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WO2023050829A1 - 视频帧处理方法、装置、电子设备以及存储介质 - Google Patents

视频帧处理方法、装置、电子设备以及存储介质 Download PDF

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Publication number
WO2023050829A1
WO2023050829A1 PCT/CN2022/093457 CN2022093457W WO2023050829A1 WO 2023050829 A1 WO2023050829 A1 WO 2023050829A1 CN 2022093457 W CN2022093457 W CN 2022093457W WO 2023050829 A1 WO2023050829 A1 WO 2023050829A1
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WIPO (PCT)
Prior art keywords
video frame
image
attribute value
configuration information
target
Prior art date
Application number
PCT/CN2022/093457
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English (en)
French (fr)
Inventor
张演龙
胡伟东
张琦
Original Assignee
北京百度网讯科技有限公司
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Application filed by 北京百度网讯科技有限公司 filed Critical 北京百度网讯科技有限公司
Priority to US18/020,832 priority Critical patent/US20240305736A1/en
Publication of WO2023050829A1 publication Critical patent/WO2023050829A1/zh

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/234Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/46Colour picture communication systems
    • H04N1/56Processing of colour picture signals
    • H04N1/60Colour correction or control
    • H04N1/6002Corrections within particular colour systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/20Image enhancement or restoration using local operators
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/40Extraction of image or video features
    • G06V10/56Extraction of image or video features relating to colour
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/40Extraction of image or video features
    • G06V10/60Extraction of image or video features relating to illumination properties, e.g. using a reflectance or lighting model
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/234Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
    • H04N21/2347Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving video stream encryption
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/80Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
    • H04N21/81Monomedia components thereof
    • H04N21/8166Monomedia components thereof involving executable data, e.g. software
    • H04N21/8193Monomedia components thereof involving executable data, e.g. software dedicated tools, e.g. video decoder software or IPMP tool

Definitions

  • the present disclosure relates to the technical field of artificial intelligence, in particular to the technical field of computer vision and deep learning, and can be applied to scenarios such as image processing and image recognition. Specifically, it relates to a video frame processing method, device, electronic equipment and storage medium.
  • the disclosure provides a video frame processing method, device, electronic equipment and storage medium.
  • a video frame processing method including: determining enhancement configuration information in response to an image enhancement request for an initial video frame, wherein the enhancement configuration information includes the The current attribute value of at least one image attribute is adjusted to the information related to the target attribute value; and, based on the above-mentioned enhanced configuration information, an image enhancement tool is used to adjust the current attribute value of at least one image attribute of the above-mentioned initial video frame to obtain the target video frame, wherein , the above image enhancement tools support encryption.
  • a video frame processing device including: a response module, configured to determine enhancement configuration information in response to an image enhancement request for an initial video frame, wherein the above enhancement configuration information includes information used for Adjusting the current attribute value of at least one image attribute of the initial video frame to information related to the target attribute value; and an adjustment module, configured to use an image enhancement tool to adjust at least one image attribute of the initial video frame based on the enhanced configuration information The current attribute value of , to obtain the target video frame, wherein the above-mentioned image enhancement tool supports the encryption function.
  • an electronic device including: at least one processor; and a memory communicated with the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by Executing by at least one processor to enable the at least one processor to perform the method as described above.
  • a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the above method.
  • a computer program product comprising a computer program which, when executed by a processor, implements the method as described above.
  • FIG. 1 schematically shows an exemplary system architecture to which a video frame processing method and a processing device can be applied according to an embodiment of the present disclosure
  • Fig. 2 schematically shows a flow chart of a video frame processing method according to an embodiment of the present disclosure
  • Fig. 3 schematically shows a schematic diagram of a video frame processing process according to an embodiment of the present disclosure
  • Fig. 4 schematically shows a block diagram of a video frame processing device according to an embodiment of the present disclosure.
  • Fig. 5 schematically shows a block diagram of an electronic device suitable for a video frame processing method according to an embodiment of the present disclosure.
  • image acquisition process it may be affected by factors such as the intensity of ambient light and the performance of the display device, resulting in low contrast, color distortion, and low definition of the image, which is very important for users to visually observe and analyze. Bringing difficulties, therefore, image enhancement is required for the image.
  • Image enhancement can highlight the features of interest in the image or suppress some unwanted features in the image according to the predetermined needs, so that the image matches the visual response characteristics.
  • Image enhancement can be a preprocessing operation of image analysis and image processing.
  • a video can include multiple video frames, each video frame being an image.
  • Image enhancement for mobile terminals can be implemented in the following ways.
  • One way is to use an image enhancement tool developed based on OpenGL Shader to perform image enhancement processing on the video frame before decoding the video.
  • Another way is to perform a preprocessing operation after the video is decoded, and use a deep learning model to perform image enhancement processing on the preprocessed video frame.
  • OpengGL Shader is easier to be cracked by third-party software.
  • the third-party software can be QualcommProfiler.
  • QualcommProfiler can be used to obtain the specific implementation of the image enhancement tool developed based on OpenGL Shader. Therefore, the security of the image enhancement implemented by the above method is low.
  • the terminal device is required to have a high-performance CPU or GPU (Graphics Processing Unit, graphics processing unit), so as to effectively ensure the real-time performance of image enhancement. Since the performance of the terminal equipment is not high, the real-time performance of the image enhancement implemented by the above another method is poor.
  • a high-performance CPU or GPU Graphics Processing Unit, graphics processing unit
  • the embodiment of the present disclosure proposes a solution for image enhancement using an image enhancement tool capable of implementing an encryption function. That is, enhancement configuration information is determined in response to an image enhancement request for an initial video frame.
  • the enhanced configuration information includes information related to adjusting the current attribute value of at least one image attribute of the initial video frame to a target attribute value, and based on the enhanced configuration information, an image enhancement tool that supports an encryption function is used to adjust at least one of the initial video frame.
  • Image enhancement tools can support encryption functions. Therefore, the process of using the image enhancement tool to adjust the current attribute value of the image attribute of the initial video frame to the target attribute value to obtain the target video frame is relatively difficult to be cracked, thereby improving the security of image enhancement.
  • the deep learning model is not used to achieve image enhancement, the performance requirements of the terminal equipment are not high. Therefore, the real-time performance of image enhancement can be effectively guaranteed when the performance of the terminal device is not high.
  • Fig. 1 schematically shows an exemplary system architecture to which a video frame processing method and a processing device can be applied according to an embodiment of the present disclosure.
  • the exemplary system architecture that can be applied to the video frame processing method and processing device may include a terminal device, but the terminal device can implement the content processing method provided by the embodiment of the present disclosure without interacting with the server. and processing equipment.
  • a system architecture 100 may include terminal devices 101 , 102 , 103 , a network 104 and a server 105 .
  • the network 104 is used as a medium for providing communication links between the terminal devices 101 , 102 , 103 and the server 105 .
  • Network 104 may include various connection types, such as wired and/or wireless communication links, and the like.
  • Terminal devices 101 , 102 , 103 Users can use terminal devices 101 , 102 , 103 to interact with server 105 via network 104 to receive or send messages and the like.
  • Various communication client applications can be installed on the terminal devices 101, 102, 103, such as knowledge reading applications, web browser applications, search applications, instant messaging tools, email clients and/or social platform software, etc. (only example).
  • the terminal devices 101, 102, 103 may be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers and desktop computers.
  • the server 105 may be various types of servers that provide various services, such as a background management server that supports content browsed by users using the terminal devices 101 , 102 , 103 (just an example).
  • the background management server can analyze and process received data such as user requests, and feed back processing results (such as webpages, information, or data obtained or generated according to user requests) to the terminal device.
  • the server 105 can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, which solves the management difficulties in traditional physical hosts and VPS services (Virtual Private Server, VPS). Large and weak business expansion.
  • the server 105 can also be a server of a distributed system, or a server combined with blockchain.
  • the video frame processing method provided by the embodiment of the present disclosure may be executed by the terminal device 101 , 102 , or 103 .
  • the video frame processing apparatus provided by the embodiment of the present disclosure may also be set in the terminal device 101 , 102 , or 103 .
  • the video frame processing method provided by the embodiment of the present disclosure may also be executed by the server 105 .
  • the video frame processing apparatus provided by the embodiment of the present disclosure may generally be set in the server 105 .
  • the video frame processing method provided by the embodiments of the present disclosure may also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101 , 102 , 103 and/or the server 105 .
  • the video frame processing apparatus provided by the embodiments of the present disclosure may also be set in a server or a server cluster that is different from the server 105 and can communicate with the terminal devices 101 , 102 , 103 and/or the server 105 .
  • the server 105 determines the enhancement configuration information in response to the image enhancement request for the initial video frame, and uses an image enhancement tool to adjust the current attribute value of at least one image attribute of the initial video frame based on the enhancement configuration information to obtain the target video frame.
  • a server or server cluster capable of communicating with the terminal devices 101, 102, 103 and/or the server 105 responds to the image enhancement request for the initial video frame, and finally obtains the target video frame.
  • terminal devices, networks and servers in Fig. 1 are only illustrative. According to the implementation needs, there can be any number of terminal devices, networks and servers.
  • Fig. 2 schematically shows a flowchart of a video frame processing method according to an embodiment of the present disclosure.
  • the method 200 may include operations S210-S220.
  • enhancement configuration information is determined in response to an image enhancement request for an initial video frame.
  • the enhancement configuration information includes information related to adjusting a current property value of at least one image property of the initial video frame to a target property value.
  • an image enhancement tool is used to adjust a current attribute value of at least one image attribute of the initial video frame to obtain a target video frame.
  • the image enhancement tool supports encryption function.
  • a video may include a plurality of video frames arranged according to time stamps.
  • the initial video frame may be any one of multiple video frames included in the video.
  • the image enhancement request may be a request to process image enhancement.
  • the enhancement configuration information may include information for adjusting a property value of at least one image property of the initial video frame from a current property value to a target property value.
  • the initial video frame may refer to a video frame before image enhancement processing.
  • the target video frame may refer to a video frame after image enhancement processing.
  • the image properties may include at least one of the following: image brightness, image sharpness, image saturation, image contrast and image resolution.
  • the current attribute value may refer to an attribute value corresponding to an image attribute in the initial video frame.
  • the target attribute value may refer to an attribute value corresponding to an image attribute in the target video frame.
  • the enhanced configuration information may include at least one of the following: brightness configuration information, sharpness configuration information, saturation configuration information, contrast configuration information, and resolution configuration information.
  • the image enhancement tool may be an image enhancement tool developed based on a development language and capable of supporting an encryption function.
  • the development language may include an open computing language (namely OpenCL) or Metal language.
  • OpenCL open computing language
  • Metal language namely OpenCL
  • "The image enhancement tool supports an encryption function” may mean that the image enhancement tool itself is encrypted.
  • the image enhancement tool itself is encrypted may mean that the specific implementation of the image enhancement tool cannot be obtained from outside.
  • the image enhancement tool supports the encryption function may mean that the image enhancement tool itself is not encrypted, but uses an authentication policy to implement encryption.
  • the image enhancement tool supports encryption for using an identity authentication policy, that is, the trusted users who can use the image enhancement tool to perform image enhancement can be pre-determined.
  • a user may be characterized by a user identification.
  • Authentication policies can be used to verify whether a user is a trusted user.
  • an image enhancement tool may be used to perform image enhancement processing.
  • an image enhancement request for an initial video frame may be obtained, and enhancement configuration information may be determined in response to the image enhancement request.
  • determining the enhancement configuration information may include: parsing the image enhancement request to obtain the enhancement configuration information, that is, the image enhancement request may carry the enhancement configuration information.
  • the enhancement configuration information corresponding to the image enhancement request is generated according to the information of the image enhancement request.
  • the image enhancement tool may be invoked, and for each image attribute in at least one image attribute, based on the enhancement configuration information corresponding to the image attribute, the image enhancement tool is used to convert the image attribute to The current attribute value is adjusted to the target attribute value. Under the condition that the current attribute value of each image attribute is adjusted to the target attribute value, the image enhancement operation for the initial video frame is completed to obtain the target video frame. That is, the attribute value of each image attribute in the target video frame is the target attribute value.
  • the enhancement configuration information in response to an image enhancement request for an initial video frame, is determined, based on the enhancement configuration information, an image enhancement tool supporting an encryption function is used to adjust the current attribute value of at least one image attribute of the initial video frame, Get the target video frame.
  • Image enhancement tools can support encryption functions. Therefore, the process of using the image enhancement tool to adjust the current attribute value of the image attribute of the initial video frame to the target attribute value to obtain the target video frame is relatively difficult to be cracked, thereby improving the security of image enhancement.
  • the deep learning model is not used to achieve image enhancement, and the performance requirements of the terminal equipment are not high. Therefore, the real-time performance of image enhancement can be effectively guaranteed when the performance of the terminal device is not high.
  • the above video frame processing method may further include the following operations.
  • the source code corresponding to the image enhancement operation may refer to a code obtained by writing the image enhancement operation based on a development language.
  • the development language may include open computing language or Metal language.
  • the corresponding development language can be selected according to the operating system of the terminal device. For example, if the operating system of the terminal device is Android, an image enhancement tool can be developed based on an open computing language. If the operating system of the terminal device is an iOS system, an image enhancement tool can be developed based on the Metal language.
  • a library file may include resources related to image enhancement operations, such as functions and variables.
  • Library files can include static library files and dynamic library files.
  • the image enhancement operation can be obtained, and the source code corresponding to the image enhancement operation can be determined.
  • the source code can be compiled by a compiler to obtain a library file, and the Library files identified as image enhancement tools.
  • the image enhancement tool in the form of a library file makes the specific implementation of the image enhancement tool inaccessible to the outside. Therefore, the process of using the image enhancement tool to adjust the current attribute value of the image attribute of the initial video frame to the target attribute value to obtain the target video frame is relatively difficult to be cracked, thereby improving the security of image enhancement.
  • operation S210 may include the following operations.
  • the respective current attribute values of the plurality of image attributes of the initial video frame are respectively adjusted to obtain the target video frame.
  • the preset processing order may refer to an order in which image enhancement operations are performed on a plurality of image attributes.
  • the preset processing sequence can be configured according to actual business requirements, which is not limited here.
  • image attributes may include image brightness, image sharpness, and image saturation.
  • the preset processing sequence may be a processing sequence obtained by permuting and combining image enhancement operations for image brightness, image enhancement operations for image clarity, and image enhancement operations for image saturation.
  • the preset processing order may be sequentially processed in the following order, that is, an image enhancement operation for image definition, an image enhancement operation for image brightness, and an image enhancement operation for image saturation.
  • the preset processing order may be sequentially processed in the following order, that is, an image enhancement operation for image saturation, an image enhancement operation for image brightness, and an image enhancement operation for image definition.
  • the preset processing order may be sequentially processed in the following order, that is, an image enhancement operation for image definition, an image enhancement operation for image brightness, and an image enhancement operation for image saturation.
  • processing the current attribute values of the plurality of image attributes of the initial video frame respectively to obtain the target video frame may include: converting the initial video frame from the first color space to the second color space, obtaining The first intermediate video frame.
  • the resolution configuration information the current attribute value of the image resolution of the first intermediate video frame is adjusted to a target attribute value to obtain a fifth intermediate video frame.
  • the current attribute value of image brightness of the fifth intermediate video frame is adjusted to a target attribute value to obtain a sixth intermediate video frame. Converting the sixth intermediate video frame from the second color space to the first color space results in a seventh intermediate video frame.
  • the current attribute value of the image saturation of the seventh intermediate video frame is adjusted to the target attribute value to obtain the target video frame.
  • the plurality of image attributes include image brightness, image sharpness, and image saturation.
  • the enhanced configuration information includes brightness configuration information, sharpness configuration information and saturation configuration information.
  • processing respective current attribute values of multiple image attributes of the initial video frame to obtain the target video frame may include the following operations.
  • the initial video frame is converted from the first color space to the second color space to obtain a first intermediate video frame.
  • the current attribute value of the image brightness of the first intermediate video frame is adjusted to a target attribute value to obtain a second intermediate video frame.
  • the sharpness configuration information the current attribute value of the image sharpness of the second intermediate video frame is adjusted to a target attribute value to obtain a third intermediate video frame.
  • the current attribute value of the image saturation of the fourth intermediate video frame is adjusted to the target attribute value to obtain the target video frame.
  • the brightness configuration information may be enhancement configuration information corresponding to an image enhancement operation for image brightness of a video frame.
  • the brightness configuration information may include at least one piece of mapping relationship information, and each piece of mapping relationship information represents a mapping relationship between a pre-adjustment value and an adjusted value of image brightness.
  • the brightness configuration information may include a brightness mapping function.
  • the sharpness configuration information may be enhancement configuration information corresponding to an image enhancement operation on the sharpness of the video frame.
  • the saturation configuration information may be enhancement configuration information corresponding to an image enhancement operation on the saturation of the video frame.
  • the first color space conversion routine may be called, and the initial video frame is converted from the first color space to the second color space by using the first color space conversion routine to obtain the first intermediate video frame.
  • the current attribute value of the image brightness of the first intermediate video frame may be adjusted to the target attribute value based on the brightness configuration information, and obtaining the second intermediate video frame may include: based on the brightness mapping function, adjusting the first intermediate video frame
  • the current attribute value of the image brightness of an intermediate video frame is adjusted to the target attribute value to obtain the second intermediate video frame, that is, the current attribute value of the image brightness of the first intermediate video frame is input into the brightness mapping function to obtain the attribute value of the image brightness is the second intermediate video frame of the target attribute value.
  • a pre-adjustment value matching the current attribute value of image brightness is searched from at least one piece of mapping relationship information.
  • the post-adjustment value having a mapping relationship with the target pre-adjustment value is determined as the target attribute value corresponding to the image brightness.
  • the current attribute value of the image brightness of the first intermediate video frame is adjusted to the target attribute value to obtain the second intermediate video frame.
  • the current attribute value of the image sharpness of the second intermediate video frame may be adjusted to a target attribute value based on the definition configuration information to obtain a third intermediate video frame, Then call the second color space conversion routine, use the second color space conversion routine to convert the third intermediate video frame from the second color space to the first color space, obtain the fourth intermediate video frame, and finally configure the information based on the saturation , adjusting the current attribute value of the image saturation of the fourth intermediate video frame to the target attribute value to obtain the target video frame.
  • the current attribute value of the image attribute can be dynamically adjusted as required to obtain a target video frame for image enhancement. Therefore, the image quality can be improved, thereby improving the user's viewing experience.
  • video streams with the same image quality can save network transmission bandwidth and reduce traffic.
  • the brightness configuration information includes at least one piece of mapping relationship information, and each piece of mapping relationship information represents a mapping relationship between a pre-adjustment value and an adjusted value of image brightness.
  • adjusting the current attribute value of the image brightness of the first intermediate video frame to a target attribute value based on the brightness configuration information to obtain the second intermediate video frame may include the following operations.
  • a pre-adjustment value matching the current attribute value of the brightness of the image is searched from at least one piece of mapping relation information.
  • the post-adjustment value having a mapping relationship with the target pre-adjustment value is determined as the target attribute value corresponding to the image brightness.
  • the current attribute value of the image brightness of the first intermediate video frame is adjusted to the target attribute value to obtain the second intermediate video frame.
  • the current attribute value of image brightness is the current attribute value a.
  • the current attribute value a matches the pre-adjustment value b.
  • the unadjusted value matching the current attribute value a of image brightness is the unadjusted value b.
  • the adjusted value c having a mapping relationship with the unadjusted value b is determined as the target attribute value of image brightness.
  • the current attribute value a of the image brightness of the first intermediate video is adjusted to the target attribute value, that is, adjusted to the adjusted value c, to obtain the second intermediate video frame.
  • the sharpness configuration information includes denoising parameters.
  • adjusting the current attribute value of the image definition of the second intermediate video frame to the target attribute value based on the definition configuration information to obtain the third intermediate video frame may include the following operations.
  • the denoising parameters may include mean denoising parameters, median denoising parameters or Gaussian denoising parameters. It can be configured according to actual business requirements, which is not limited here.
  • the saturation configuration information includes a saturation coefficient.
  • adjusting the current attribute value of the image saturation of the fourth intermediate video frame to the target attribute value based on the saturation configuration information to obtain the target video frame may include the following operations.
  • the current attribute value of the image saturation of the fourth intermediate video frame is adjusted to a target attribute value to obtain a target video frame.
  • the saturation coefficient may be used to adjust the current attribute value of image saturation to a target attribute value.
  • the saturation coefficient can be configured according to actual service requirements, which is not limited here.
  • the saturation factor may be 1.65.
  • the current property value of image saturation may include a first current component value, a second current component value, and a third current component value.
  • the current attribute value of the image saturation of the fourth intermediate video frame is adjusted to the target attribute value to obtain the target video frame It may include: under the condition of keeping the third current component value of the image saturation of the fourth intermediate video frame unchanged, combining the saturation coefficient with the first current component value and the second component value of the image saturation of the fourth intermediate video frame respectively The current component values are multiplied to obtain the target video frame.
  • the target attribute value of image saturation includes the third current component value, the value obtained by multiplying the first current component value by the saturation coefficient, and the value obtained by multiplying the second current component value by the saturation coefficient.
  • the first color space includes a YUV color space
  • the second color space includes a BGR color space
  • the YUV color space may be a color space in which a color is described by a luminance-color difference.
  • the YUV color space may include Y (Luminance, brightness), U (Chrominance, chroma) and V (Chroma, density).
  • the BGR color space may include B (Blue, blue), G (Green, green), and R (Red, red).
  • the current attribute value of image saturation may include a first current component value, a second current component value, and a third current component value.
  • the first current component value may be a U component value.
  • the second current component value may be a V component value.
  • the third current component value may include a Y component value.
  • the current attribute value of the image saturation of the fourth intermediate video frame is adjusted to the target attribute value, and obtaining the target video frame may include: maintaining the fourth When the Y component value of the image saturation of the intermediate video frame is constant, the saturation coefficient is multiplied with the U component value of the image saturation of the fourth intermediate video frame and the value of the image saturation of the fourth intermediate video frame The V component values are multiplied to obtain the target video frame.
  • Fig. 3 schematically shows a schematic diagram of a video frame processing process according to an embodiment of the present disclosure.
  • an initial video frame 301 is converted from a first color space 302 to a second color space 303 to obtain a first intermediate video frame 304 .
  • the current attribute value of image brightness of the first intermediate video frame 304 is adjusted to a target attribute value to obtain a second intermediate video frame 305 .
  • the current attribute value of the image resolution of the second intermediate video frame 305 is adjusted to a target attribute value to obtain a third intermediate video frame 306 .
  • the third intermediate video frame 306 is converted from the second color space 303 to the first color space 302 to obtain a fourth intermediate video frame 307 .
  • the current attribute value of the image saturation of the fourth intermediate video frame 307 is adjusted to a target attribute value to obtain a target video frame 308 .
  • Fig. 4 schematically shows a block diagram of a video frame processing device according to an embodiment of the present disclosure.
  • the video frame processing apparatus 400 may include a response module 410 and an adjustment module 420 .
  • the response module 410 is configured to determine enhancement configuration information in response to the image enhancement request for the initial video frame.
  • the enhancement configuration information includes information related to adjusting a current property value of at least one image property of the initial video frame to a target property value.
  • the adjustment module 420 is configured to use an image enhancement tool to adjust the current attribute value of at least one image attribute of the initial video frame to obtain a target video frame based on the enhancement configuration information, wherein the image enhancement tool supports an encryption function.
  • the video frame processing apparatus 400 may further include a first determining module, a compiling module and a second determining module.
  • the first determination module is used to determine the source code corresponding to the image enhancement operation.
  • the compilation module is used to compile the source code to obtain the library file.
  • the adjustment module 420 may include an adjustment sub-module.
  • the plurality of image attributes include image brightness, image sharpness, and image saturation.
  • the enhanced configuration information includes brightness configuration information, sharpness configuration information and saturation configuration information.
  • the adjustment sub-module may include a first conversion unit, a first adjustment unit, a second adjustment unit, a second conversion unit and a third adjustment unit.
  • the first converting unit is configured to convert the initial video frame from the first color space to the second color space to obtain the first intermediate video frame.
  • the first adjustment unit is configured to adjust the current attribute value of the image brightness of the first intermediate video frame to a target attribute value based on the brightness configuration information to obtain the second intermediate video frame.
  • the second adjustment unit is configured to adjust the current attribute value of the image definition of the second intermediate video frame to a target attribute value based on the definition configuration information to obtain a third intermediate video frame.
  • the second conversion unit is configured to convert the third intermediate video frame from the second color space to the first color space to obtain a fourth intermediate video frame.
  • the third adjustment unit is configured to adjust the current attribute value of the image saturation of the fourth intermediate video frame to a target attribute value based on the saturation configuration information to obtain the target video frame.
  • the brightness configuration information includes at least one piece of mapping relationship information, and each piece of mapping relationship information represents a mapping relationship between a pre-adjustment value and an adjusted value of image brightness.
  • the first adjustment unit may include a search subunit, a determination subunit, and a first adjustment subunit.
  • the search subunit is configured to, according to the current value of the image brightness, search for a pre-adjustment value matching the current attribute value of the image brightness from at least one piece of mapping relationship information.
  • the determination subunit is used to determine the adjusted value having a mapping relationship with the target value before adjustment as the target attribute value corresponding to the image brightness.
  • the first adjustment subunit is configured to adjust the current attribute value of the image brightness of the first intermediate video frame to a target attribute value to obtain a second intermediate video frame.
  • the sharpness configuration information includes denoising parameters.
  • the second adjusting unit may include an obtaining subunit.
  • a subunit is obtained, configured to convolve the second intermediate video frame with a denoising parameter to obtain a third intermediate video frame.
  • the saturation configuration information includes a saturation coefficient.
  • the third adjustment unit may include a second adjustment subunit.
  • the first color space includes a YUV color space
  • the second color space includes a BGR color space
  • the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.
  • an electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by at least one processor, and the instructions are processed by at least one The processor is executed, so that at least one processor can perform the method as described above.
  • non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the method as described above.
  • a computer program product includes a computer program, and the computer program implements the above method when executed by a processor.
  • the device 500 includes a computing unit 501 that can execute according to a computer program stored in a read-only memory (ROM) 502 or loaded from a storage unit 508 into a random-access memory (RAM) 503. Various appropriate actions and treatments. In the RAM 503, various programs and data necessary for the operation of the device 500 can also be stored.
  • the computing unit 501, ROM 502, and RAM 503 are connected to each other through a bus 504.
  • An input/output (I/O) interface 505 is also connected to the bus 504 .
  • the I/O interface 505 includes: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a magnetic disk, an optical disk, etc. ; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, and the like.
  • the communication unit 509 allows the device 500 to exchange information/data with other devices over a computer network such as the Internet and/or various telecommunication networks.
  • the computing unit 501 may be various general-purpose and/or special-purpose processing components having processing and computing capabilities. Some examples of computing units 501 include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processing processor (DSP), and any suitable processor, controller, microcontroller, etc.
  • the computing unit 501 executes various methods and processes described above, such as video frame processing methods.
  • the video frame processing method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 508 .
  • part or all of the computer program may be loaded and/or installed on the device 500 via the ROM 502 and/or the communication unit 509 .
  • the computer program When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the video frame processing method described above can be performed.
  • the computing unit 501 may be configured to execute the video frame processing method in any other suitable manner (for example, by means of firmware).
  • Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips Implemented in a system of systems (SOC), complex programmable logic device (CPLD), computer hardware, firmware, software, and/or combinations thereof.
  • FPGAs field programmable gate arrays
  • ASICs application specific integrated circuits
  • ASSPs application specific standard products
  • SOC system of systems
  • CPLD complex programmable logic device
  • computer hardware firmware, software, and/or combinations thereof.
  • programmable processor can be special-purpose or general-purpose programmable processor, can receive data and instruction from storage system, at least one input device, and at least one output device, and transmit data and instruction to this storage system, this at least one input device, and this at least one output device an output device.
  • Program codes for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special purpose computer, or other programmable data processing devices, so that the program codes, when executed by the processor or controller, make the functions/functions specified in the flow diagrams and/or block diagrams Action is implemented.
  • the program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
  • a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device.
  • a machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium.
  • a machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing.
  • machine-readable storage media would include one or more wire-based electrical connections, portable computer discs, hard drives, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, compact disk read only memory (CD-ROM), optical storage, magnetic storage, or any suitable combination of the foregoing.
  • RAM random access memory
  • ROM read only memory
  • EPROM or flash memory erasable programmable read only memory
  • CD-ROM compact disk read only memory
  • magnetic storage or any suitable combination of the foregoing.
  • the systems and techniques described herein can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user. ); and a keyboard and pointing device (eg, a mouse or a trackball) through which a user can provide input to the computer.
  • a display device e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor
  • a keyboard and pointing device eg, a mouse or a trackball
  • Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and can be in any form (including Acoustic input, speech input or, tactile input) to receive input from the user.
  • the systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., as a a user computer having a graphical user interface or web browser through which a user can interact with embodiments of the systems and techniques described herein), or including such backend components, middleware components, Or any combination of front-end components in a computing system.
  • the components of the system can be interconnected by any form or medium of digital data communication, eg, a communication network. Examples of communication networks include: Local Area Network (LAN), Wide Area Network (WAN) and the Internet.
  • a computer system may include clients and servers.
  • Clients and servers are generally remote from each other and typically interact through a communication network.
  • the relationship of client and server arises by computer programs running on the respective computers and having a client-server relationship to each other.
  • the server can be a cloud server, a server of a distributed system, or a server combined with a blockchain.

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Abstract

本公开提供了一种视频帧处理方法、装置、电子设备以及存储介质,涉及人工智能技术领域,尤其涉及计算机视觉和深度学习技术领域,可应用于图像处理、图像识别等场景。具体实现方案为:响应于针对初始视频帧的图像增强请求,确定增强配置信息,其中,增强配置信息包括与用于将初始视频帧的至少一个图像属性的当前属性值调整至目标属性值相关的信息。基于增强配置信息,利用图像增强工具调整初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧,其中,图像增强工具支持加密功能。

Description

视频帧处理方法、装置、电子设备以及存储介质
本申请要求于2021年9月29日提交的、申请号为202111156586.7的中国专利申请的优先权,其全部内容通过引用结合在本公开中。
技术领域
本公开涉及人工智能技术领域,尤其涉及计算机视觉和深度学习技术领域,可应用于图像处理、图像识别等场景。具体地,涉及一种视频帧处理方法、装置、电子设备以及存储介质。
背景技术
计算机视觉技术和视频技术等在各个领域有着广泛的应用。例如,视频娱乐、远程视频聊天、自动辅助驾驶和交通安全监控等。在这些应用中进行着各种图像数据的获得,获得的图像数据将进行展示,以满足应用需求。
发明内容
本公开提供了一种视频帧处理方法、装置、电子设备以及存储介质。
根据本公开的一方面,提供了一种视频帧处理方法,包括:响应于针对初始视频帧的图像增强请求,确定增强配置信息,其中,上述增强配置信息包括与用于将上述初始视频帧的至少一个图像属性的当前属性值调整至目标属性值相关的信息;以及,基于上述增强配置信息,利用图像增强工具调整上述初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧,其中,上述图像增强工具支持加密功能。
根据本公开的另一方面,提供了一种视频帧处理装置,包括:响应模块,用于响应于针对初始视频帧的图像增强请求,确定增强配置信息,其中,上述增强配置信息包括与用于将上述初始视频帧的至少一个图像属性的当前属性值调整至目标属性值相关的信息;以及,调整模块,用于基于上述增强配置信息,利用图像增强工具调整上述初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧,其中,上述图像增强工具支持加密功能。
根据本公开的另一方面,提供了一种电子设备,包括:至少一个处理器;以及 与至少一个处理器通信连接的存储器;其中,存储器存储有可被至少一个处理器执行的指令,指令被至少一个处理器执行,以使至少一个处理器能够执行如上所述的方法。
根据本公开的另一方面,提供了一种存储有计算机指令的非瞬时计算机可读存储介质,其中,计算机指令用于使计算机执行如上所述的方法。
根据本公开的另一方面,提供了一种计算机程序产品,包括计算机程序,计算机程序在被处理器执行时实现如上所述的方法。
应当理解,本部分所描述的内容并非旨在标识本公开的实施例的关键或重要特征,也不用于限制本公开的范围。本公开的其它特征将通过以下的说明书而变得容易理解。
附图说明
附图用于更好地理解本方案,不构成对本公开的限定。其中:
图1示意性示出了根据本公开实施例的可以应用视频帧处理方法及处理装置的示例性系统架构;
图2示意性示出了根据本公开实施例的视频帧处理方法的流程图;
图3示意性示出了根据本公开实施例的视频帧处理过程的示意图;
图4示意性示出了根据本公开实施例的视频帧处理装置的框图;以及
图5示意性示出了根据本公开实施例的适用于视频帧处理方法的电子设备的框图。
具体实施方式
以下结合附图对本公开的示范性实施例做出说明,其中包括本公开实施例的各种细节以助于理解,应当将它们认为仅仅是示范性的。因此,本领域普通技术人员应当认识到,可以对这里描述的实施例做出各种改变和修改,而不会背离本公开的范围和精神。同样,为了清楚和简明,以下的描述中省略了对公知功能和结构的描述。
图像在获取的过程中有可能会受到环境光线强弱和显示设备的性能等因素的影响,导致图像出现对比度较低、颜色失真和清晰度较低等现象,给用户视觉观察和及其分析处理带来困难,因此,需要对图像进行图像增强。
图像增强可以根据预定需要突出图像中感兴趣的特征或者抑制图像中某些不 需要的特征,使得图像与视觉响应特性相匹配的方法。图像增强可以是图像分析和图像处理的预处理操作。视频可以包括多个视频帧,每个视频帧是一个图像。
针对移动端的图像增强,可以利用如下方式实现。
一种方式在于,在将视频进行解码之前,利用基于OpenGL Shader开发的图像增强工具对视频帧进行图像增强处理。
另一种方式在于,在将视频进行解码之后进行预处理操作,利用深度学习模型对预处理后的视频帧进行图像增强处理。
在实现本公开构思的过程中,发现针对上述一种方式,OpengGL Shader较容易被第三方软件破解。例如,第三方软件可以为SnapdragonProfiler。可以利用SnapdragonProfiler获取基于OpenGL Shader开发的图像增强工具的具体实现,因此,利用上述一种方式实现的图像增强的安全性较低。
针对另一种方式,需要终端设备具有较高性能的CPU或GPU(Graphics Processing Unit,图形处理器),以有效保证图像增强的实时性。由于终端设备的性能不高,因此,利用上述另一种方式实现的图像增强的实时性较差。
为此,本公开实施例提出了一种利用能够实现加密功能的图像增强工具进行图像增强的方案。即,响应于针对初始视频帧的图像增强请求,确定增强配置信息。增强配置信息包括与用于将初始视频帧的至少一个图像属性的当前属性值调整至目标属性值相关的信息,并基于增强配置信息,利用支持加密功能的图像增强工具调整初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧。图像增强工具能够支持加密功能。因此,利用图像增强工具调整初始视频帧的图像属性的当前属性值至目标属性值得到目标视频帧的过程较难以被破解,由此提高了图像增强的安全性。此外,由于未利用深度学习模型实现图像增强,对终端设备的性能要求不高。因此,能够在终端设备的性能不高的情况下,有效保证图像增强的实时性。
图1示意性示出了根据本公开实施例的可以应用视频帧处理方法及处理装置的示例性系统架构。
需要注意的是,图1所示仅为可以应用本公开实施例的系统架构的示例,以帮助本领域技术人员理解本公开的技术内容,但并不意味着本公开实施例不可以用于其他设备、系统、环境或场景。例如,在另一实施例中,可以应用视频帧处理方法及处理装置的示例性系统架构可以包括终端设备,但终端设备可以无需与服务器进 行交互,即可实现本公开实施例提供的内容处理方法及处理装置。
如图1所示,根据该实施例的系统架构100可以包括终端设备101、102、103,网络104和服务器105。网络104用以在终端设备101、102、103和服务器105之间提供通信链路的介质。网络104可以包括各种连接类型,例如有线和/或无线通信链路等。
用户可以使用终端设备101、102、103通过网络104与服务器105交互,以接收或发送消息等。终端设备101、102、103上可以安装有各种通讯客户端应用,例如知识阅读类应用、网页浏览器应用、搜索类应用、即时通信工具、邮箱客户端和/或社交平台软件等(仅为示例)。
终端设备101、102、103可以是具有显示屏并且支持网页浏览的各种电子设备,包括但不限于智能手机、平板电脑、膝上型便携计算机和台式计算机等。
服务器105可以是提供各种服务的各种类型的服务器,例如对用户利用终端设备101、102、103所浏览的内容提供支持的后台管理服务器(仅为示例)。后台管理服务器可以对接收到的用户请求等数据进行分析等处理,并将处理结果(例如根据用户请求获取或生成的网页、信息、或数据等)反馈给终端设备。
服务器105可以是云服务器,又称为云计算服务器或云主机,是云计算服务体系中的一项主机产品,解决了传统物理主机与VPS服务(Virtual Private Server,VPS)中,存在的管理难度大,业务扩展性弱的缺陷。服务器105也可以为分布式系统的服务器,或者是结合了区块链的服务器。
需要说明的是,本公开实施例所提供的视频帧处理方法一般可以由终端设备101、102、或103执行。相应地,本公开实施例所提供的视频帧处理装置也可以设置于终端设备101、102、或103中。
或者,本公开实施例所提供的视频帧处理方法一般也可以由服务器105执行。相应地,本公开实施例所提供的视频帧处理装置一般可以设置于服务器105中。本公开实施例所提供的视频帧处理方法也可以由不同于服务器105且能够与终端设备101、102、103和/或服务器105通信的服务器或服务器集群执行。相应地,本公开实施例所提供的视频帧处理装置也可以设置于不同于服务器105且能够与终端设备101、102、103和/或服务器105通信的服务器或服务器集群中。
例如,服务器105响应于针对初始视频帧的图像增强请求,确定增强配置信息, 基于增强配置信息,利用图像增强工具调整初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧。或者由能够与终端设备101、102、103和/或服务器105通信的服务器或服务器集群响应于针对初始视频帧的图像增强请求,并最终得到目标视频帧。
应该理解,图1中的终端设备、网络和服务器的数目仅仅是示意性的。根据实现需要,可以具有任意数目的终端设备、网络和服务器。
图2示意性示出了根据本公开实施例的视频帧处理方法的流程图。
如图2所示,该方法200可以包括操作S210~S220。
在操作S210,响应于针对初始视频帧的图像增强请求,确定增强配置信息。增强配置信息包括与用于将初始视频帧的至少一个图像属性的当前属性值调整至目标属性值相关的信息。
在操作S220,基于增强配置信息,利用图像增强工具调整初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧。图像增强工具支持加密功能。
根据本公开的实施例,视频可以包括按照时间戳排列的多个视频帧。初始视频帧可以是视频包括的多个视频帧中的任意一个视频帧。图像增强请求可以是用于请求处理图像增强的请求。增强配置信息可以包括用于将初始视频帧的至少一个图像属性的属性值从当前属性值调整至目标属性值的信息。初始视频帧可以指图像增强处理前的视频帧。目标视频帧可以指图像增强处理后的视频帧。图像属性可以包括以下至少一项:图像亮度、图像清晰度、图像饱和度、图像对比度和图像分辨率。当前属性值可以指与初始视频帧中图像属性对应的属性值。目标属性值可以指与目标视频帧中图像属性对应的属性值。相应的,增强配置信息可以包括以下至少一项:亮度配置信息、清晰度配置信息、饱和度配置信息、对比度配置信息和分辨率配置信息。
根据本公开的实施例,图像增强工具可以是基于开发语言开发的,能够支持加密功能的图像增强工具。开发语言可以包括开放运算语言(即OpenCL)或Metal语言。“图像增强工具支持加密功能”可以是指图像增强工具本身是加密的。“图像增强工具本身是加密”的可以指外部不能获得图像增强工具的具体实现。备选地,“图像增强工具支持加密功能”可以是指图像增强工具本身是不加密的,而是利用身份验证策略实现加密。
根据本公开的实施例,针对利用身份验证策略实现图像增强工具支持加密,即,可以预先确定能够利用图像增强工具进行图像增强的可信用户。可以利用用户标识表征用户。身份验证策略可以用于验证用户是否是可信用户的策略。响应于用户的身份验证请求,在确定身份验证请求包括的用户标识是可信用户标识的情况下,确定与用户标识对应的用户是可信用户。在确定用户是可信用户的情况下,可以利用图像增强工具进行图像增强处理。
根据本公开的实施例,可以获取针对初始视频帧的图像增强请求,响应于图像增强请求,确定增强配置信息。响应于图像增强请求,确定增强配置信息可以包括:对图像增强请求进行解析,得到增强配置信息,即,图像增强请求可以携带有增强配置信息。备选地,响应于图像增强请求,根据图像增强请求的信息,生成与图像增强请求对应的增强配置信息。
根据本公开的实施例,在确定增强配置信息之后,可以调用图像增强工具,针对至少一个图像属性中的每个图像属性,基于与图像属性对应的增强配置信息,利用图像增强工具将图像属性的当前属性值调整至目标属性值。在将每个图像属性的当前属性值调整至目标属性值的情况下,完成针对初始视频帧的图像增强操作,得到目标视频帧。即,目标视频帧中每个图像属性的属性值是目标属性值。
根据本公开的实施例,响应于针对初始视频帧的图像增强请求,确定增强配置信息,基于增强配置信息,利用支持加密功能的图像增强工具调整初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧。图像增强工具能够支持加密功能。因此,利用图像增强工具调整初始视频帧的图像属性的当前属性值至目标属性值得到目标视频帧的过程较难以被破解,由此提高了图像增强的安全性。此外,未利用深度学习模型实现图像增强,对终端设备的性能要求不高。因此,能够在终端设备的性能不高的情况下,有效保证图像增强的实时性。
根据本公开的实施例,上述视频帧处理方法还可以包括如下操作。
确定与图像增强操作对应的源代码。将源代码进行编译得到库文件。将库文件确定为图像增强工具。
根据本公开的实施例,与图像增强操作对应的源代码可以指基于开发语言对图像增强操作进行编写得到的代码。开发语言可以包括开放运算语言或Metal语言。可以根据终端设备的操作系统选择相应的开发语言。例如,如果终端设备的操作系 统是安卓系统,则可以基于开放运算语言开发图像增强工具。如果终端设备的操作系统是iOS系统,则可以基于Metal语言开发图像增强工具。
根据本公开的实施例,库文件可以包括与图像增强操作相关的资源,例如,函数和变量。库文件可以包括静态库文件和动态库文件。
根据本公开的实施例,可以获取图像增强操作,确定与图像增强操作对应的源代码,在确定与图像增强操作对应的源代码之后,可以利用编译器对源代码进行编译,得到库文件,将库文件确定为图像增强工具。
根据本公开的实施例,库文件形式的图像增强工具使得外部不能够获得图像增强工具的具体实现。因此,利用图像增强工具调整初始视频帧的图像属性的当前属性值至目标属性值得到目标视频帧的过程较难以被破解,由此提高了图像增强的安全性。
根据本公开的实施例,操作S210可以包括如下操作。
基于预设处理顺序和增强配置信息,分别调整初始视频帧的多个图像属性各自的当前属性值,得到目标视频帧。
根据本公开的实施例,预设处理顺序可以指对多个图像属性进行图像增强操作的顺序。预设处理顺序可以根据实际业务需求进行配置,在此不作限定。例如,图像属性可以包括图像亮度、图像清晰度和图像饱和度。预设处理顺序可以是针对图像亮度的图像增强操作、针对图像清晰度的图像增强操作和针对图像饱和度的图像增强操作进行排列组合得到的处理顺序。例如,预设处理处理顺序可以是按照如下顺序依次处理,即,针对图像清晰度的图像增强操作、针对图像亮度的图像增强操作和针对图像饱和度的图像增强操作。预设处理顺序可以是按照如下顺序依次处理,即,针对图像饱和度的图像增强操作、针对图像亮度的图像增强操作和针对图像清晰度的图像增强操作。
根据本公开的实施例,预设处理处理顺序可以是按照如下顺序依次处理,即,针对图像清晰度的图像增强操作、针对图像亮度的图像增强操作和针对图像饱和度的图像增强操作。基于预设处理顺序和增强配置信息,分别处理初始视频帧的多个图像属性各自的当前属性值,得到目标视频帧可以包括:将初始视频帧从第一颜色空间转换至第二颜色空间,得到第一中间视频帧。基于清晰度配置信息,将第一中间视频帧的图像清晰度的当前属性值调整至目标属性值,得到第五中间视频帧。基 于亮度配置信息,将第五中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第六中间视频帧。将第六中间视频帧从第二颜色空间转换至第一颜色空间,得到第七中间视频帧。基于饱和度配置信息,将第七中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧。
根据本公开的实施例,多个图像属性包括图像亮度、图像清晰度和图像饱和度。增强配置信息包括亮度配置信息、清晰度配置信息和饱和度配置信息。
根据本公开的实施例,基于预设处理顺序和增强配置信息,分别处理初始视频帧的多个图像属性各自的当前属性值,得到目标视频帧可以包括如下操作。
将初始视频帧从第一颜色空间转换至第二颜色空间,得到第一中间视频帧。基于亮度配置信息,将第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧。基于清晰度配置信息,将第二中间视频帧的图像清晰度的当前属性值调整至目标属性值,得到第三中间视频帧。将第三中间视频帧从第二颜色空间转换至第一颜色空间,得到第四中间视频帧。基于饱和度配置信息,将第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧。
根据本公开的实施例,亮度配置信息可以是与用于对视频帧的图像亮度进行图像增强操作对应的增强配置信息。亮度配置信息可以包括至少一个映射关系信息,每个映射关系信息表征图像亮度的调整前值与调整后值的映射关系。备选地,亮度配置信息可以包括亮度映射函数。清晰度配置信息可以是与用于对视频帧的清晰度进行图像增强操作对应的增强配置信息。饱和度配置信息可以是与用于对视频帧的饱和度进行图像增强操作对应的增强配置信息。
根据本公开的实施例,第一颜色空间可以包括HSV颜色空间、YUV颜色空间或其他包含亮度信息的颜色空间。第二颜色空间可以包括BGR颜色空间、RGB颜色空间或其他颜色空间。
根据本公开的实施例,可以调用第一颜色空间转换例程,利用第一颜色空间转换例程,将初始视频帧从第一颜色空间转换至第二颜色空间,得到第一中间视频帧。在获得第一中间视频帧之后,可以基于亮度配置信息,将第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧可以包括:基于亮度映射函数,将第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧,即,将第一中间视频帧的图像亮度的当前属性值输入亮度映射函数,得 到图像亮度的属性值是目标属性值的第二中间视频帧。备选地,根据图像亮度的当前值,从至少一个映射关系信息中查找与图像亮度的当前属性值相匹配的调整前值。将与目标调整前值具有映射关系的调整后值确定为与图像亮度对应的目标属性值。将第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧。
根据本公开的实施例,在获得第一中间视频帧之后,可以基于清晰度配置信息,将第二中间视频帧的图像清晰度的当前属性值调整至目标属性值,得到第三中间视频帧,再调用第二颜色空间转换例程,利用第二颜色空间转换例程,将第三中间视频帧从第二颜色空间转换至第一颜色空间,得到第四中间视频帧,最后基于饱和度配置信息,将第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧。
根据本公开的实施例,基于增强配置信息,可以根据需要动态调整图像属性的当前属性值,得到图像增强的目标视频帧。因此,可以提高图像质量,进而提高用户的观看体验。此外,同等图像质量的视频流,可以节省网络传输带宽,减少流量。
根据本公开的实施例,亮度配置信息包括至少一个映射关系信息,每个映射关系信息表征图像亮度的调整前值与调整后值的映射关系。
根据本公开的实施例,基于亮度配置信息,将第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧可以包括如下操作。
根据图像亮度的当前值,从至少一个映射关系信息中查找与图像亮度的当前属性值相匹配的调整前值。将与目标调整前值具有映射关系的调整后值确定为与图像亮度对应的目标属性值。将第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧。
根据本公开的实施例,例如,图像亮度的当前属性值是当前属性值a。图像亮度的调整前值b与调整后值c具有的映射关系。当前属性值a与调整前值b相匹配。
可以从至少一个映射关系信息中查找到与图像亮度的当前属性值a相匹配的调整前值是调整前值b。将与调整前值b具有映射关系的调整后值c确定为图像亮度的目标属性值。将第一中间视频的图像亮度的当前属性值a调整至目标属性值,即,调整至调整后值c,得到第二中间视频帧。
根据本公开的实施例,清晰度配置信息包括去噪参数。
根据本公开的实施例,基于清晰度配置信息,将第二中间视频帧的图像清晰度的当前属性值调整至目标属性值,得到第三中间视频帧,可以包括如下操作。
将第二中间视频帧与去噪参数进行卷积,得到第三中间视频帧。
根据本公开的实施例,去噪参数可以包括均值去噪参数、中值去噪参数或高斯去噪参数。可以根据实际业务需求进行配置,在此不作限定。
根据本公开的实施例,饱和度配置信息包括饱和度系数。
根据本公开的实施例,基于饱和度配置信息,将第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧,可以包括如下操作。
基于第四中间视频帧的图像饱和度的当前属性值与饱和度系数,将第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧。
根据本公开的实施例,饱和度系数可以用于实现将图像饱和度的当前属性值调整至目标属性值。饱和度系数可以根据实际业务需求进行配置,在此不作限定。例如,饱和度系数可以是1.65。图像饱和度的当前属性值可以包括第一当前分量值、第二当前分量值和第三当前分量值。
根据本公开的实施例,基于第四中间视频帧的图像饱和度的当前属性值与饱和度系数,将第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧可以包括:在保持第四中间视频帧的图像饱和度的第三当前分量值不变的情况下,将饱和度系数分别与第四中间视频帧的图像饱和度的第一当前分量值和第二当前分量值进行相乘,得到目标视频帧。图像饱和度的目标属性值包括第三当前分量值、第一当前分量值与饱和度系数相乘后得到的值和第二当前分量值与饱和度系数相乘后得到的值。
根据本公开的实施例,第一颜色空间包括YUV颜色空间,第二颜色空间包括BGR颜色空间。
根据本公开的实施例,YUV颜色空间可以是通过亮度-色差来描述颜色的颜色空间。YUV颜色空间可以包括Y(Luminance,亮度)、U(Chrominance,色度)和V(Chroma,浓度)。BGR颜色空间可以包括B(Blue,蓝色)、G(Green,绿色)和R(Red,红色)。
根据本公开的实施例,在第一颜色空间是YUV颜色空间的情况下,图像饱和度的当前属性值可以包括第一当前分量值、第二当前分量值和第三当前分量值。第 一当前分量值可以是U分量值。第二当前分量值可以是V分量值。第三当前分量值可以包括Y分量值。基于第四中间视频帧的图像饱和度的当前属性值与饱和度系数,将第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧可以包括:在保持第四中间视频帧的图像饱和度的Y分量值不变的情况下,将饱和度系数分别与第四中间视频帧的图像饱和度的U分量值相乘以及与第四中间视频帧的图像饱和度的V分量值相乘,得到目标视频帧。
下面参考图3,结合具体实施例对本公开实施例的视频帧处理方法做进一步说明。
图3示意性示出了根据本公开实施例的视频帧处理过程的示意图。
如图3所示,在300中,将初始视频帧301从第一颜色空间302转换至第二颜色空间303,得到第一中间视频帧304。基于亮度配置信息,将第一中间视频帧304的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧305。基于清晰度配置信息,将第二中间视频帧305的图像清晰度的当前属性值调整至目标属性值,得到第三中间视频帧306。将第三中间视频帧306从第二颜色空间303转换至第一颜色空间302,得到第四中间视频帧307。基于饱和度配置信息,将第四中间视频帧307的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧308。
以上仅是示例性实施例,但不限于此,还可以包括本领域已知的其他视频帧处理方法,只要能够实现视频帧的处理即可。
图4示意性示出了根据本公开实施例的视频帧处理装置的框图。
如图4所示,视频帧处理装置400可以包括响应模块410和调整模块420。
响应模块410,用于响应于针对初始视频帧的图像增强请求,确定增强配置信息。增强配置信息包括与用于将初始视频帧的至少一个图像属性的当前属性值调整至目标属性值相关的信息。
调整模块420,用于基于增强配置信息,利用图像增强工具调整初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧,其中,图像增强工具支持加密功能。
根据本公开的实施例,上述视频帧处理装置400还可以还包括第一确定模块、编译模块和第二确定模块。
第一确定模块,用于确定与图像增强操作对应的源代码。
编译模块,用于将源代码进行编译得到库文件。
第二确定模块,用于将库文件确定为图像增强工具。
根据本公开的实施例,调整模块420可以包括调整子模块。
调整子模块,用于基于预设处理顺序和增强配置信息,分别调整初始视频帧的多个图像属性各自的当前属性值,得到目标视频帧。
根据本公开的实施例,多个图像属性包括图像亮度、图像清晰度和图像饱和度。增强配置信息包括亮度配置信息、清晰度配置信息和饱和度配置信息。
根据本公开的实施例,调整子模块可以包括第一转换单元、第一调整单元、第二调整单元、第二转换单元和第三调整单元。
第一转换单元,用于将初始视频帧从第一颜色空间转换至第二颜色空间,得到第一中间视频帧。
第一调整单元,用于基于亮度配置信息,将第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧。
第二调整单元,用于基于清晰度配置信息,将第二中间视频帧的图像清晰度的当前属性值调整至目标属性值,得到第三中间视频帧。
第二转换单元,用于将第三中间视频帧从第二颜色空间转换至第一颜色空间,得到第四中间视频帧。
第三调整单元,用于基于饱和度配置信息,将第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧。
根据本公开的实施例,亮度配置信息包括至少一个映射关系信息,每个映射关系信息表征图像亮度的调整前值与调整后值的映射关系。
根据本公开的实施例,第一调整单元可以包括查找子单元、确定子单元和第一调整子单元。
查找子单元,用于根据图像亮度的当前值,从至少一个映射关系信息中查找与图像亮度的当前属性值相匹配的调整前值。
确定子单元,用于将与目标调整前值具有映射关系的调整后值确定为与图像亮度对应的目标属性值。
第一调整子单元,用于将第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧。
根据本公开的实施例,清晰度配置信息包括去噪参数。
根据本公开的实施例,第二调整单元可以包括获得子单元。
获得子单元,用于将第二中间视频帧与去噪参数进行卷积,得到第三中间视频帧。
根据本公开的实施例,饱和度配置信息包括饱和度系数。
根据本公开的实施例,第三调整单元可以包括第二调整子单元。
第二调整子单元,用于基于第四中间视频帧的图像饱和度的当前属性值与饱和度系数,将第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到目标视频帧。
根据本公开的实施例,第一颜色空间包括YUV颜色空间,第二颜色空间包括BGR颜色空间。
根据本公开的实施例,本公开还提供了一种电子设备、一种可读存储介质和一种计算机程序产品。
根据本公开的实施例,一种电子设备,包括:至少一个处理器;以及与至少一个处理器通信连接的存储器;其中,存储器存储有可被至少一个处理器执行的指令,指令被至少一个处理器执行,以使至少一个处理器能够执行如上所述的方法。
根据本公开的实施例,一种存储有计算机指令的非瞬时计算机可读存储介质,其中,计算机指令用于使计算机执行如上所述的方法。
根据本公开的实施例,一种计算机程序产品,包括计算机程序,计算机程序在被处理器执行时实现如上所述的方法。
图5示意性示出了根据本公开实施例的适用于视频帧处理方法的电子设备的框图。电子设备500旨在表示各种形式的数字计算机,诸如,膝上型计算机、台式计算机、工作台、个人数字助理、服务器、刀片式服务器、大型计算机、和其它适合的计算机。电子设备还可以表示各种形式的移动装置,诸如,个人数字处理、蜂窝电话、智能电话、可穿戴设备和其它类似的计算装置。本文所示的部件、它们的连接和关系、以及它们的功能仅仅作为示例,并且不意在限制本文中描述的和/或者要求的本公开的实现。
如图5所示,设备500包括计算单元501,其可以根据存储在只读存储器(ROM)502中的计算机程序或者从存储单元508加载到随机访问存储器(RAM)503中的计 算机程序,来执行各种适当的动作和处理。在RAM 503中,还可存储设备500操作所需的各种程序和数据。计算单元501、ROM 502以及RAM 503通过总线504彼此相连。输入/输出(I/O)接口505也连接至总线504。
设备500中的多个部件连接至I/O接口505,包括:输入单元506,例如键盘、鼠标等;输出单元507,例如各种类型的显示器、扬声器等;存储单元508,例如磁盘、光盘等;以及通信单元509,例如网卡、调制解调器、无线通信收发机等。通信单元509允许设备500通过诸如因特网的计算机网络和/或各种电信网络与其他设备交换信息/数据。
计算单元501可以是各种具有处理和计算能力的通用和/或专用处理组件。计算单元501的一些示例包括但不限于中央处理单元(CPU)、图形处理单元(GPU)、各种专用的人工智能(AI)计算芯片、各种运行机器学习模型算法的计算单元、数字信号处理器(DSP)、以及任何适当的处理器、控制器、微控制器等。计算单元501执行上文所描述的各个方法和处理,例如视频帧处理方法。例如,在一些实施例中,视频帧处理方法可被实现为计算机软件程序,其被有形地包含于机器可读介质,例如存储单元508。在一些实施例中,计算机程序的部分或者全部可以经由ROM502和/或通信单元509而被载入和/或安装到设备500上。当计算机程序加载到RAM503并由计算单元501执行时,可以执行上文描述的视频帧处理方法的一个或多个步骤。备选地,在其他实施例中,计算单元501可以通过其他任何适当的方式(例如,借助于固件)而被配置为执行视频帧处理方法。
本文中以上描述的系统和技术的各种实施方式可以在数字电子电路系统、集成电路系统、场可编程门阵列(FPGA)、专用集成电路(ASIC)、专用标准产品(ASSP)、芯片上系统的系统(SOC)、复杂可编程逻辑设备(CPLD)、计算机硬件、固件、软件、和/或它们的组合中实现。这些各种实施方式可以包括:实施在一个或者多个计算机程序中,该一个或者多个计算机程序可在包括至少一个可编程处理器的可编程系统上执行和/或解释,该可编程处理器可以是专用或者通用可编程处理器,可以从存储系统、至少一个输入装置、和至少一个输出装置接收数据和指令,并且将数据和指令传输至该存储系统、该至少一个输入装置、和该至少一个输出装置。
用于实施本公开的方法的程序代码可以采用一个或多个编程语言的任何组合来编写。这些程序代码可以提供给通用计算机、专用计算机或其他可编程数据处理 装置的处理器或控制器,使得程序代码当由处理器或控制器执行时使流程图和/或框图中所规定的功能/操作被实施。程序代码可以完全在机器上执行、部分地在机器上执行,作为独立软件包部分地在机器上执行且部分地在远程机器上执行或完全在远程机器或服务器上执行。
在本公开的上下文中,机器可读介质可以是有形的介质,其可以包含或存储以供指令执行系统、装置或设备使用或与指令执行系统、装置或设备结合地使用的程序。机器可读介质可以是机器可读信号介质或机器可读储存介质。机器可读介质可以包括但不限于电子的、磁性的、光学的、电磁的、红外的、或半导体系统、装置或设备,或者上述内容的任何合适组合。机器可读存储介质的更具体示例会包括基于一个或多个线的电气连接、便携式计算机盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦除可编程只读存储器(EPROM或快闪存储器)、光纤、便捷式紧凑盘只读存储器(CD-ROM)、光学储存设备、磁储存设备、或上述内容的任何合适组合。
为了提供与用户的交互,可以在计算机上实施此处描述的系统和技术,该计算机具有:用于向用户显示信息的显示装置(例如,CRT(阴极射线管)或者LCD(液晶显示器)监视器);以及键盘和指向装置(例如,鼠标或者轨迹球),用户可以通过该键盘和该指向装置来将输入提供给计算机。其它种类的装置还可以用于提供与用户的交互;例如,提供给用户的反馈可以是任何形式的传感反馈(例如,视觉反馈、听觉反馈、或者触觉反馈);并且可以用任何形式(包括声输入、语音输入或者、触觉输入)来接收来自用户的输入。
可以将此处描述的系统和技术实施在包括后台部件的计算系统(例如,作为数据服务器)、或者包括中间件部件的计算系统(例如,应用服务器)、或者包括前端部件的计算系统(例如,具有图形用户界面或者网络浏览器的用户计算机,用户可以通过该图形用户界面或者该网络浏览器来与此处描述的系统和技术的实施方式交互)、或者包括这种后台部件、中间件部件、或者前端部件的任何组合的计算系统中。可以通过任何形式或者介质的数字数据通信(例如,通信网络)来将系统的部件相互连接。通信网络的示例包括:局域网(LAN)、广域网(WAN)和互联网。
计算机系统可以包括客户端和服务器。客户端和服务器一般远离彼此并且通常 通过通信网络进行交互。通过在相应的计算机上运行并且彼此具有客户端-服务器关系的计算机程序来产生客户端和服务器的关系。服务器可以是云服务器,也可以是分布式系统的服务器,或者是结合了区块链的服务器。
应该理解,可以使用上面所示的各种形式的流程,重新排序、增加或删除步骤。例如,本发公开中记载的各步骤可以并行地执行也可以顺序地执行也可以不同的次序执行,只要能够实现本公开公开的技术方案所期望的结果,本文在此不进行限制。上述具体实施方式,并不构成对本公开保护范围的限制。本领域技术人员应该明白的是,根据设计要求和其他因素,可以进行各种修改、组合、子组合和替代。任何在本公开的精神和原则之内所作的修改、等同替换和改进等,均应包含在本公开保护范围之内。

Claims (19)

  1. 一种视频帧处理方法,包括:
    响应于针对初始视频帧的图像增强请求,确定增强配置信息,其中,所述增强配置信息包括与用于将所述初始视频帧的至少一个图像属性的当前属性值调整至目标属性值相关的信息;以及
    基于所述增强配置信息,利用图像增强工具调整所述初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧,其中,所述图像增强工具支持加密功能。
  2. 根据权利要求1所述的方法,还包括:
    确定与图像增强操作对应的源代码;
    将所述源代码进行编译得到库文件;以及
    将所述库文件确定为所述图像增强工具。
  3. 根据权利要求1或2所述的方法,其中,所述基于所述增强配置信息,利用图像增强工具调整所述初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧,包括:
    基于预设处理顺序和所述增强配置信息,分别调整所述初始视频帧的多个所述图像属性各自的当前属性值,得到所述目标视频帧。
  4. 根据权利要求3所述的方法,其中,多个所述图像属性包括图像亮度、图像清晰度和图像饱和度;
    所述增强配置信息包括亮度配置信息、清晰度配置信息和饱和度配置信息;
    所述基于预设处理顺序和所述增强配置信息,分别处理所述初始视频帧的多个所述图像属性各自的当前属性值,得到所述目标视频帧,包括:
    将所述初始视频帧从第一颜色空间转换至第二颜色空间,得到第一中间视频帧;
    基于所述亮度配置信息,将所述第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧;
    基于所述清晰度配置信息,将所述第二中间视频帧的图像清晰度的当前属性值调整至目标属性值,得到第三中间视频帧;
    将所述第三中间视频帧从所述第二颜色空间转换至所述第一颜色空间,得到第四中间视频帧;以及
    基于所述饱和度配置信息,将所述第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到所述目标视频帧。
  5. 根据权利要求4所述的方法,其中,所述亮度配置信息包括至少一个映射关系信息,每个所述映射关系信息表征所述图像亮度的调整前值与调整后值的映射关系;
    所述基于所述亮度配置信息,将所述第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧,包括:
    根据所述图像亮度的当前值,从所述至少一个映射关系信息中查找与所述图像亮度的当前属性值相匹配的调整前值;
    将与所述目标调整前值具有所述映射关系的调整后值确定为与所述图像亮度对应的目标属性值;以及
    将所述第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到所述第二中间视频帧。
  6. 根据权利要求4或5所述的方法,其中,所述清晰度配置信息包括去噪参数;
    所述基于所述清晰度配置信息,将所述第二中间视频帧的图像清晰度的当前属性值调整至目标属性值,得到第三中间视频帧,包括:
    将所述第二中间视频帧与所述去噪参数进行卷积,得到所述第三中间视频帧。
  7. 根据权利要求4~6中任一项所述的方法,其中,所述饱和度配置信息包括饱和度系数;
    所述基于所述饱和度配置信息,将所述第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到所述目标视频帧,包括:
    基于所述第四中间视频帧的图像饱和度的当前属性值与所述饱和度系数,将所述第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到所述目标视频帧。
  8. 根据权利要求4~7中任一项所述的方法,其中,所述第一颜色空间包括YUV颜色空间,所述第二颜色空间包括BGR颜色空间。
  9. 一种视频帧处理装置,包括:
    响应模块,用于响应于针对初始视频帧的图像增强请求,确定增强配置信息,其中,所述增强配置信息包括与用于将所述初始视频帧的至少一个图像属性的当前属性值调整至目标属性值相关的信息;以及
    调整模块,用于基于所述增强配置信息,利用图像增强工具调整所述初始视频帧的至少一个图像属性的当前属性值,得到目标视频帧,其中,所述图像增强工具支持加密功能。
  10. 根据权利要求9所述的装置,还包括:
    第一确定模块,用于确定与图像增强操作对应的源代码;
    编译模块,用于将所述源代码进行编译得到库文件;以及
    第二确定模块,用于将所述库文件确定为所述图像增强工具。
  11. 根据权利要求9或10所述的装置,其中,所述调整模块,包括:
    调整子模块,用于基于预设处理顺序和所述增强配置信息,分别调整所述初始视频帧的多个所述图像属性各自的当前属性值,得到所述目标视频帧。
  12. 根据权利要求11所述的装置,其中,多个所述图像属性包括图像亮度、图像清晰度和图像饱和度;
    所述增强配置信息包括亮度配置信息、清晰度配置信息和饱和度配置信息;
    所述调整子模块,包括:
    第一转换单元,用于将所述初始视频帧从第一颜色空间转换至第二颜色空间,得到第一中间视频帧;
    第一调整单元,用于基于所述亮度配置信息,将所述第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到第二中间视频帧;
    第二调整单元,用于基于所述清晰度配置信息,将所述第二中间视频帧的图像清晰度的当前属性值调整至目标属性值,得到第三中间视频帧;
    第二转换单元,用于将所述第三中间视频帧从所述第二颜色空间转换至所述第一颜色空间,得到第四中间视频帧;以及
    第三调整单元,用于基于所述饱和度配置信息,将所述第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到所述目标视频帧。
  13. 根据权利要求12所述的装置,其中,所述亮度配置信息包括至少一个映射关系信息,每个所述映射关系信息表征所述图像亮度的调整前值与调整后值的映射关系;
    所述第一调整单元,包括:
    查找子单元,用于根据所述图像亮度的当前值,从所述至少一个映射关系信息中查找与所述图像亮度的当前属性值相匹配的调整前值;
    确定子单元,用于将与所述目标调整前值具有所述映射关系的调整后值确定为与所述图像亮度对应的目标属性值;以及
    第一调整子单元,用于将所述第一中间视频帧的图像亮度的当前属性值调整至目标属性值,得到所述第二中间视频帧。
  14. 根据权利要求12或13所述的装置,其中,所述清晰度配置信息包括去噪参数;
    所述第二调整单元,包括:
    获得子单元,用于将所述第二中间视频帧与所述去噪参数进行卷积,得到所述第三中间视频帧。
  15. 根据权利要求12~14中任一项所述的装置,其中,所述饱和度配置信息包括饱和度系数;
    所述第三调整单元,包括:
    第二调整子单元,用于基于所述第四中间视频帧的图像饱和度的当前属性值与所述饱和度系数,将所述第四中间视频帧的图像饱和度的当前属性值调整至目标属性值,得到所述目标视频帧。
  16. 根据权利要求12~15中任一项所述的装置,其中,所述第一颜色空间包括YUV颜色空间,所述第二颜色空间包括BGR颜色空间。
  17. 一种电子设备,包括:
    至少一个处理器;以及
    与所述至少一个处理器通信连接的存储器;其中,
    所述存储器存储有可被所述至少一个处理器执行的指令,所述指令被所述至少一个处理器执行,以使所述至少一个处理器能够执行权利要求1~8中任一项所述的方法。
  18. 一种存储有计算机指令的非瞬时计算机可读存储介质,其中,所述计算机指令用于使所述计算机执行根据权利要求1~8中任一项所述的方法。
  19. 一种计算机程序产品,包括计算机程序,所述计算机程序在被处理器执行时实现根据权利要求1~8中任一项所述的方法。
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