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CN104902271A - Prediction mode selection method and device - Google Patents

Prediction mode selection method and device Download PDF

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Publication number
CN104902271A
CN104902271A CN201510249916.5A CN201510249916A CN104902271A CN 104902271 A CN104902271 A CN 104902271A CN 201510249916 A CN201510249916 A CN 201510249916A CN 104902271 A CN104902271 A CN 104902271A
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rate distortion
distortion costs
pattern
interframe
merge
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CN104902271B (en
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周俊明
简伟华
侯慧慧
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Tencent Technology Beijing Co Ltd
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Tencent Technology Beijing Co Ltd
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Abstract

The invention discloses a prediction mode selection method and device, and belongs to the field of video coding. The method comprises the steps: respectively calculating the rate-distortion costs Jskip, Jmerge and J2N*2N when a current prediction unit employs an inter-frame skip mode, an inter-frame merge mode and an inter-frame J2N*2N mode; detecting whether the rate-distortion cost Jskip is less than the rate-distortion costs Jmerge and J2N*2N or not; setting the rate-distortion cost Jskip as a candidate rate-distortion cost Jmode when the rate-distortion cost Jskip is less than the rate-distortion costs Jmerge and J2N*2N; calculating a rate-distortion cost Jintera when the current prediction unit employs at least one inter-frame prediction mode; and selecting the prediction mode with the minimum rate-distortion cost from the rate-distortion costs Jmode and Jintera. The method and device skip the rate-distortion cost calculation process of other seven inter-frame prediction modes when the inter-frame skip mode is better, and can effectively reduce the time consumption of prediction mode selection.

Description

Predicting mode selecting method and device
Technical field
The present invention relates to field of video encoding, particularly a kind of predicting mode selecting method and device.
Background technology
In HEVC (High Efficient Video Coding, high efficiency Video coding) standard, (Prediction Unit is called for short: concept PU) to propose predicting unit.Predicting unit is the elementary cell of carrying out inter prediction and infra-frame prediction.
In HEVC standard, provide several inter-frame forecast mode and several intra prediction mode is available.In order to find optimum predictive mode, prior art needs to calculate the rate distortion costs of current prediction unit under each predictive mode, and selects the minimum predictive mode of rate distortion costs as the final predictive mode adopted.
Realizing in process of the present invention, inventor finds that prior art at least exists following problem: owing to needing to calculate the rate distortion costs under each predictive mode, and the amount of calculation of rate distortion costs is larger, cause the selection course of predictive mode to need to spend more consuming time, account for whole cataloged procedure consuming time 60% ~ 70%.
Summary of the invention
In order to solve the problem of prior art, embodiments provide a kind of predicting mode selecting method and device.Described technical scheme is as follows:
According to first aspect of the present disclosure, provide a kind of predicting mode selecting method, described method comprises:
Calculate the rate distortion costs J of current prediction unit when adopting interframe skip pattern respectively skip, adopt interframe merge pattern time rate distortion costs J mergewith the rate distortion costs J adopted under interframe 2N*2N pattern 2N*2N;
Detect described J skipwhether be less than described J mergewith described J 2N*2N;
If described J skipbe less than described J mergewith described J 2N*2N, then by described J skipbe set to candidate rate distortion costs J mode;
Calculate the rate distortion costs J of described current prediction unit when adopting at least one intra prediction mode intra;
From described J modewith J described at least one intrain select the final predictive mode of the minimum predictive mode of rate distortion costs as described current prediction unit.
According to second aspect of the present disclosure, provide a kind of prediction mode selection apparatus, described device comprises:
First computing module, for calculating the rate distortion costs J of current prediction unit when adopting interframe skip pattern respectively skip, adopt interframe merge pattern time rate distortion costs J mergewith the rate distortion costs J adopted under interframe 2N*2N pattern 2N*2N;
Skip detection module, for detecting described J skipwhether be less than described J mergewith described J 2N*2N;
Skip and module is set, if for described J skipbe less than described J mergewith described J 2N*2N, then by described J skipbe set to candidate rate distortion costs J mode;
Second computing module, also for calculating the rate distortion costs J of described current prediction unit when adopting at least one intra prediction mode intra;
Final decision module, for from described J modewith J described at least one intrain select the final predictive mode of the minimum predictive mode of rate distortion costs as described current prediction unit.
The beneficial effect that the technical scheme that the embodiment of the present invention provides is brought is:
By when interframe skip pattern is more excellent, skip the rate distortion costs computational process of other the 7 kinds of inter-frame forecast modes except interframe skip pattern, interframe merge pattern and interframe 2N*2N pattern, decrease the amount of calculation required for predictive mode selection course, effectively can reduce the consuming time of predictive mode selection, meet the demand of the higher scene of some requirement of real-times.
Accompanying drawing explanation
In order to be illustrated more clearly in the technical scheme in the embodiment of the present invention, below the accompanying drawing used required in describing embodiment is briefly described, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the division schematic diagram of 8 kinds of inter-frame forecast modes of the predicting unit that the embodiment of the present invention relates to;
Fig. 2 is the method flow diagram of the predicting mode selecting method that one embodiment of the invention provides;
Fig. 3 is the method flow diagram of the predicting mode selecting method that another embodiment of the present invention provides;
Fig. 4 is the structural representation of the prediction mode selection apparatus that one embodiment of the invention provides;
Fig. 5 is the structural representation of the prediction mode selection apparatus that another embodiment of the present invention provides.
Embodiment
For making the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, embodiment of the present invention is described further in detail.
First brief introduction is carried out to the several nouns involved by the present embodiment:
Picture frame: one section of video is made up of some two field picture frames.Video compression coding generally takes block-based coded system, namely the two field picture frame in video is divided into the block of multiple non-overlapping copies, encodes afterwards to these blocks.Each picture frame can adopt prediction interframe encoding mode or intraframe predictive coding mode when Video coding.
In HEVC standard, propose the concept of coding unit, predicting unit and converter unit.
Coding unit: be the elementary cell of carrying out in a picture frame encoding.Coding unit can be the block of pixels of 64*64.
Predicting unit: be the elementary cell carrying out in a picture frame predicting.Predicting unit can be the block of the Pixel Dimensions such as 64*64,32*32,16*16,8*8.
Converter unit: be the elementary cell presenting residual error (Residual) or conversion coefficient (Transform Coefficients) in a picture frame.Converter unit also can be the block of the Pixel Dimensions such as 32*32,16*16,8*8,4*4.Do not relate to the discussion of coding unit and converter unit herein.
For a predicting unit, in HEVC standard, provide 10 kinds of inter-frame forecast modes and 3 kinds of intra prediction modes.
10 kinds of inter-frame forecast modes comprise: interframe skip pattern, interframe merge pattern, interframe 2N*2N pattern, interframe N*N pattern, interframe 2N*N pattern, interframe N*2N pattern, interframe 2N*UD pattern, interframe 2N*nD pattern, interframe nL*2N pattern, interframe nR*2N pattern, as shown in Figure 1.
Wherein, interframe 2N*2N pattern, interframe N*N pattern, interframe 2N*N pattern, interframe N*2N pattern belong to four kinds of symmetrical prediction mode; Interframe 2N*UD pattern and interframe 2N*nD pattern belong to the asymmetric prediction mode of horizontal direction; Interframe nL*2N pattern, interframe nR*2N pattern belong to the asymmetric prediction mode of vertical direction.
3 kinds of intra prediction modes comprise: PCM pattern in N*N pattern and frame in 2N*2N pattern, frame in frame.
In HEVC standard, when the optimal prediction modes of decision-making current prediction unit, rate distortion costs corresponding respectively when needing to calculate the above-mentioned 13 kinds of predictive modes of current prediction unit employing, amount of calculation is very large, cause the selection course of predictive mode to need to spend more consuming time, account for whole cataloged procedure consuming time 60% ~ 70%.
Please refer to Fig. 2, it illustrates the method flow diagram of the predicting mode selecting method that one embodiment of the invention provides.The present embodiment is applied in video encoder with this predicting mode selecting method and illustrates.The method comprises:
Step 201, calculates the rate distortion costs J of current prediction unit when adopting interframe skip pattern respectively skip, adopt interframe merge pattern time rate distortion costs J mergewith the rate distortion costs J adopted under interframe 2N*2N pattern 2N*2N;
Rate distortion costs is the abbreviation of rate-distortion optimization (Rate – distortion optimization is called for short RDO) cost.The computational process of rate distortion costs is prior art, repeats no more herein.
Step 202, detects J skipwhether be less than J mergeand J 2N*2N;
Step 203, if J skipbe less than J mergeand J 2N*2N, then by J skipbe set to candidate rate distortion costs J mode;
Step 204, calculates the rate distortion costs J of current prediction unit when adopting at least one intra prediction mode intra;
Step 205, from J modewith at least one J intrain select the final predictive mode of the minimum predictive mode of rate distortion costs as current prediction unit.
In sum, the predicting mode selecting method that the present embodiment provides, when interframe skip pattern is more excellent, skip the rate distortion costs computational process of other the 7 kinds of inter-frame forecast modes except interframe skip pattern, interframe merge pattern and interframe 2N*2N pattern, decrease the amount of calculation required for predictive mode selection course, effectively can reduce the consuming time of predictive mode selection, meet the demand of the higher scene of some requirement of real-times.
Please refer to Fig. 3, it illustrates the method flow diagram of the predicting mode selecting method that another embodiment of the present invention provides.The present embodiment is applied in video encoder with this predicting mode selecting method and illustrates.The method comprises:
Step 301, calculates the rate distortion costs J of current prediction unit when adopting interframe skip pattern respectively skip, adopt interframe merge pattern time rate distortion costs J mergewith the rate distortion costs J adopted under interframe 2N*2N pattern 2N*2N;
Step 302, detects J skipwhether be less than J mergeand J 2N*2N;
If J skipbe less than J mergeand J 2N*2N, then step 303 is entered;
If J skipbe not less than J mergeand J 2N*2N, then step 304 is entered.
Step 303, by J skipbe set to candidate rate distortion costs J mode;
Step 304, calculates the rate distortion costs J of current prediction unit when adopting interframe N*N pattern respectively n*N, adopt interframe 2N*N pattern time rate distortion costs J 2N*Nwith the rate distortion costs J adopted under interframe N*2N pattern n*2N.
Step 305, from J merge, J 2N*2N, J n*N, J 2N*Nand J n*2Nin find out the first minimum value;
If the first minimum value is J merge, then step 306 is entered.
If the first minimum value is not J merge, then step 307 is entered.
Step 306, is set to candidate rate distortion costs J by the first minimum value mode;
Step 307, detects the asymmetric predictive mode whether opening horizontal direction and/or vertical direction;
Whether open the asymmetric predictive mode of horizontal direction and/or vertical direction in video encoder, preset by external encode parameter.
If both do not opened the asymmetric predictive mode of horizontal direction, do not open the asymmetric predictive mode of vertical direction yet, then entered step 306.
If only open the asymmetric predictive mode of horizontal direction, then enter step 308;
If only open the asymmetric predictive mode of vertical direction, then enter step 310;
If open the asymmetric predictive mode of horizontal direction and vertical direction simultaneously, then enter step 316.
Step 308, calculates the rate distortion costs J of current prediction unit when adopting interframe 2N*nU pattern respectively 2N*nU, adopt interframe 2N*nD pattern time rate distortion costs J 2N*nD;
Step 309, from the first minimum value, J 2N*nUand J 2N*nDin find out the second minimum value;
Step 310, calculates the rate distortion costs J of current prediction unit when adopting interframe nL*2N pattern respectively nL*2N, adopt interframe nR*2N pattern time rate distortion costs J nR*2N;
Step 311, from the first minimum value, J nL*2Nand J nR*2Nin find out the second minimum value;
Step 312, is set to candidate rate distortion costs J by the second minimum value mode;
Step 313, calculates the rate distortion costs J of current prediction unit when adopting interframe 2N*nU pattern respectively 2N*nU, adopt interframe 2N*nD pattern time rate distortion costs J 2N*nD, adopt interframe nL*2N pattern time rate distortion costs J nL*2N, adopt interframe nR*2N pattern time rate distortion costs J nR*2N;
Step 314, from the first minimum value, J 2N*nU, J 2N*nD, J nL*2Nand J nR*2Nin find out the 3rd minimum value;
Step 315, is set to candidate rate distortion costs J by the 3rd minimum value mode;
Step 316, calculates the rate distortion costs J of current prediction unit when adopting 2N*2N pattern in frame respectively intra_2N*2N, rate distortion costs J when adopting N*N pattern in frame intra_N*N, rate distortion costs J when adopting PCM pattern in frame intra_PCM;
Intra prediction mode to comprise in frame at least one in 2N*2N pattern, frame in N*N pattern and frame in PCM pattern.
Step 317, at J mode, J intra_2N*2N, J intra_N*N, J intra_PCMin select the 4th minimum value, using the final predictive mode of predictive mode corresponding for the 4th minimum value as predicting unit.
In sum, the predicting mode selecting method that the present embodiment provides, when interframe skip pattern is more excellent, skip the rate distortion costs computational process of other the 7 kinds of inter-frame forecast modes except interframe skip pattern, interframe merge pattern and interframe 2N*2N pattern, decrease the amount of calculation required for predictive mode selection course, effectively can reduce the consuming time of predictive mode selection, meet the demand of the higher scene of some requirement of real-times.
When interframe merge pattern is more excellent, even if the asymmetric predictive mode of the horizontal direction of opening and/or vertical direction, also the rate distortion costs computational process of the asymmetric predictive mode of 4 kinds of associated horizon directions and/or vertical direction is skipped, decrease the amount of calculation required for predictive mode selection course, effectively can reduce the consuming time of predictive mode selection, meet the demand of the higher scene of some requirement of real-times.
The predicting mode selecting method that the present embodiment provides has done great many of experiments in the reference software that HEVC coding standard is corresponding, under the prerequisite ensureing Image Coding quality, coding rate can be made on average to improve about 42%, and the code efficiency damage control is within 0.5%.
It should be noted that, the asymmetric predictive mode whether enabling horizontal direction and vertical direction is detected in step 306 simultaneously.In other embodiments, also first can detect the asymmetric predictive mode whether enabling horizontal direction, and then the asymmetric predictive mode whether enabling vertical direction is detected; Or, also first can detect the asymmetric predictive mode whether enabling vertical direction, and then the asymmetric predictive mode whether enabling horizontal direction is detected.The present embodiment is not specifically limited this.
Be below device embodiment of the present invention, the details do not described in detail in device embodiment, can with reference to the embodiment of the method for above-mentioned correspondence.
Please refer to Fig. 4, it illustrates the block diagram of the prediction mode selection apparatus that one embodiment of the invention provides.This prediction mode selection apparatus can realize becoming all or part of of video encoder by software, hardware or both combinations.This prediction mode selection apparatus, comprising:
First computing module 410, for calculating the rate distortion costs J of current prediction unit when adopting interframe skip pattern respectively skip, adopt interframe merge pattern time rate distortion costs J mergewith the rate distortion costs J adopted under interframe 2N*2N pattern 2N*2N;
Skip detection module 420, for detecting described J skipwhether be less than described J mergewith described J 2N*2N;
Skip and module 430 is set, if for described J skipbe less than described J mergewith described J 2N*2N, then by described J skipbe set to candidate rate distortion costs J mode;
Second computing module 440, also for calculating the rate distortion costs J of described current prediction unit when at least one intra prediction mode intra;
Final decision module 450, for from described J modewith J described at least one intrain select the final predictive mode of the minimum predictive mode of rate distortion costs as described current prediction unit.
In sum, the prediction mode selection apparatus that the present embodiment provides, when interframe skip pattern is more excellent, skip the rate distortion costs computational process of other the 7 kinds of inter-frame forecast modes except interframe skip pattern, interframe merge pattern and interframe 2N*2N pattern, decrease the amount of calculation required for predictive mode selection course, effectively can reduce the consuming time of predictive mode selection, meet the demand of the higher scene of some requirement of real-times.
Please refer to Fig. 5, it illustrates the block diagram of the prediction mode selection apparatus that one embodiment of the invention provides.This prediction mode selection apparatus can realize becoming all or part of of video encoder by software, hardware or both combinations.This prediction mode selection apparatus, comprising:
First computing module 410, for calculating the rate distortion costs J of current prediction unit when adopting interframe skip pattern respectively skip, adopt interframe merge pattern time rate distortion costs J mergewith the rate distortion costs J adopted under interframe 2N*2N pattern 2N*2N;
Skip detection module 420, for detecting described J skipwhether be less than described J mergewith described J 2N*2N;
Skip and module 430 is set, if for described J skipbe less than described J mergewith described J 2N*2N, then by described J skipbe set to candidate rate distortion costs J mode;
Second computing module 440, also for calculating the rate distortion costs J of described current prediction unit when at least one intra prediction mode intra;
Final decision module 450, for from described J modewith J described at least one intrain select the final predictive mode of the minimum predictive mode of rate distortion costs as described current prediction unit.
Alternatively, described device, also comprises:
3rd computing module 462, if also for described J skipbe not less than described J mergewith described J 2N*2N, then the rate distortion costs J of described current prediction unit when adopting interframe N*N pattern is calculated respectively n*N, adopt interframe 2N*N pattern time rate distortion costs J 2N*Nwith the rate distortion costs J adopted under interframe N*2N pattern n*2N;
First searches module 464, for from described J merge, described J 2N*2N, described J n*N, described J 2N*Nwith described J n*2Nin find out the first minimum value;
First arranges module 466, if be described J for described first minimum value merge, then by described J mergebe set to described candidate rate distortion costs J mode.
Alternatively, described device, also comprises:
Enable detection module 471, if be not described J for described first minimum value merge, then the asymmetric predictive mode whether opening horizontal direction and/or vertical direction is detected;
4th computing module 473, if the asymmetric predictive mode for only opening horizontal direction, then calculates the rate distortion costs J of described current prediction unit when adopting interframe 2N*nU pattern respectively 2N*nU, adopt interframe 2N*nD pattern time rate distortion costs J 2N*nD;
Second searches module 475, for from described first minimum value, described J 2N*nUwith described J 2N*nDin find out the second minimum value;
5th computing module 477, if the asymmetric predictive mode for only opening vertical direction, then calculates the rate distortion costs J of described current prediction unit when adopting interframe nL*2N pattern respectively nL*2N, adopt interframe nR*2N pattern time rate distortion costs J nR*2N;
Described second searches module 475, also for from described first minimum value, described J nL*2Nwith described J nR*2Nin find out described second minimum value;
Second arranges module 479, for described second minimum value is set to described candidate rate distortion costs J mode.
Alternatively, described device, also comprises:
Enable detection module 471, if be not described J for described first minimum value merge, then the asymmetric predictive mode whether described current prediction unit opens horizontal direction and/or vertical direction is detected;
6th computing module 472, if the asymmetric predictive mode for opening horizontal direction and vertical direction simultaneously, then calculates the rate distortion costs J of described current prediction unit when adopting interframe 2N*nU pattern respectively 2N*nU, adopt interframe 2N*nD pattern time rate distortion costs J 2N*nD, adopt interframe nL*2N pattern time rate distortion costs J nL*2N, adopt interframe nR*2N pattern time rate distortion costs J nR*2N;
Described 3rd searches module 474, for from described first minimum value, described J 2N*nU, described J 2N*nD, described J nL*2Nwith described J nR*2Nin find out the 3rd minimum value;
3rd arranges module 476, for described 3rd minimum value is set to described candidate rate distortion costs J mode.
Alternatively, described second computing module 440, specifically for calculating the rate distortion costs J of described current prediction unit when adopting 2N*2N pattern in frame respectively intra_2N*2N, rate distortion costs J when adopting N*N pattern in frame intra_N*N, rate distortion costs J when adopting PCM pattern in frame intra_ pCM.
In sum, the prediction mode selection apparatus that the present embodiment provides, when interframe skip pattern is more excellent, skip the rate distortion costs computational process of other the 7 kinds of inter-frame forecast modes except interframe skip pattern, interframe merge pattern and interframe 2N*2N pattern, decrease the amount of calculation required for predictive mode selection course, effectively can reduce the consuming time of predictive mode selection, meet the demand of the higher scene of some requirement of real-times.
The prediction mode selection apparatus that the present embodiment provides, also when interframe merge pattern is more excellent, even if the asymmetric predictive mode of the horizontal direction of opening and/or vertical direction, also the rate distortion costs computational process of the asymmetric predictive mode of 4 kinds of associated horizon directions and/or vertical direction is skipped, decrease the amount of calculation required for predictive mode selection course, effectively can reduce the consuming time of predictive mode selection, meet the demand of the higher scene of some requirement of real-times.
It should be noted that: the prediction mode selection apparatus that above-described embodiment provides is when triggering intelligent network service, only be illustrated with the division of above-mentioned each functional module, in practical application, can distribute as required and by above-mentioned functions and be completed by different functional modules, internal structure by equipment is divided into different functional modules, to complete all or part of function described above.In addition, the prediction mode selection apparatus that above-described embodiment provides and predicting mode selecting method embodiment belong to same design, and its specific implementation process refers to embodiment of the method, repeats no more here.
The invention described above embodiment sequence number, just to describing, does not represent the quality of embodiment.
One of ordinary skill in the art will appreciate that all or part of step realizing above-described embodiment can have been come by hardware, the hardware that also can carry out instruction relevant by program completes, described program can be stored in a kind of computer-readable recording medium, the above-mentioned storage medium mentioned can be read-only memory, disk or CD etc.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (10)

1. a predicting mode selecting method, is characterized in that, described method comprises:
Calculate the rate distortion costs J of current prediction unit when adopting interframe skip pattern respectively skip, adopt interframe merge pattern time rate distortion costs J mergewith the rate distortion costs J adopted under interframe 2N*2N pattern 2N*2N;
Detect described J skipwhether be less than described J mergewith described J 2N*2N;
If described J skipbe less than described J mergewith described J 2N*2N, then by described J skipbe set to candidate rate distortion costs J mode;
Calculate the rate distortion costs J of described current prediction unit when adopting at least one intra prediction mode intra;
From described J modewith J described at least one intrain select the final predictive mode of the minimum predictive mode of rate distortion costs as described current prediction unit.
2. method according to claim 1, is characterized in that, the described J of described detection skipwhether be less than described J mergewith described J 2N*2Nafterwards, also comprise:
If described J skipbe not less than described J mergewith described J 2N*2N, then the rate distortion costs J of described current prediction unit when adopting interframe N*N pattern is calculated respectively n*N, adopt interframe 2N*N pattern time rate distortion costs J 2N*Nwith the rate distortion costs J adopted under interframe N*2N pattern n*2N;
From described J merge, described J 2N*2N, described J n*N, described J 2N*Nwith described J n*2Nin find out the first minimum value;
If described first minimum value is described J merge, then by described J mergebe set to described candidate rate distortion costs J mode.
3. method according to claim 2, is characterized in that, described from described J merge, described J 2N*2N, described J n*N, described J 2N*Nwith described J n*2Nin find out the first minimum value after, also comprise:
If described first minimum value is not described J merge, then the asymmetric predictive mode whether opening horizontal direction and/or vertical direction is detected;
If only open the asymmetric predictive mode of horizontal direction, then calculate the rate distortion costs J of described current prediction unit when adopting interframe 2N*nU pattern respectively 2N*nU, adopt interframe 2N*nD pattern time rate distortion costs J 2N*nD; From described first minimum value, described J 2N*nUwith described J 2N*nDin find out the second minimum value;
If only open the asymmetric predictive mode of vertical direction, then calculate the rate distortion costs J of described current prediction unit when adopting interframe nL*2N pattern respectively nL*2N, adopt interframe nR*2N pattern time rate distortion costs J nR*2N; From described first minimum value, described J nL*2Nwith described J nR*2Nin find out described second minimum value;
Described second minimum value is set to described candidate rate distortion costs J mode.
4. method according to claim 2, is characterized in that, described from described J merge, described J 2N*2N, described J n*N, described J 2N*Nwith described J n*2Nin find out the first minimum value after, also comprise:
If described first minimum value is not described J merge, then the asymmetric predictive mode whether described current prediction unit opens horizontal direction and/or vertical direction is detected;
If open the asymmetric predictive mode of horizontal direction and vertical direction simultaneously, then calculate the rate distortion costs J of described current prediction unit when adopting interframe 2N*nU pattern respectively 2N*nU, adopt interframe 2N*nD pattern time rate distortion costs J 2N*nD, adopt interframe nL*2N pattern time rate distortion costs J nL*2N, adopt interframe nR*2N pattern time rate distortion costs J nR*2N;
From described first minimum value, described J 2N*nU, described J 2N*nD, described J nL*2Nwith described J nR*2Nin find out the 3rd minimum value;
Described 3rd minimum value is set to described candidate rate distortion costs J mode.
5., according to the arbitrary described method of Claims 1-4, it is characterized in that, the rate distortion costs J of the described current prediction unit of described calculating when at least one intra prediction mode intra, comprising:
Calculate the rate distortion costs J of described current prediction unit when adopting 2N*2N pattern in frame respectively intra_2N*2N, rate distortion costs J when adopting N*N pattern in frame intra_N*N, rate distortion costs J when adopting PCM pattern in frame intra_ pCM.
6. a prediction mode selection apparatus, is characterized in that, described device comprises:
First computing module, for calculating the rate distortion costs J of current prediction unit when adopting interframe skip pattern respectively skip, adopt interframe merge pattern time rate distortion costs J mergewith the rate distortion costs J adopted under interframe 2N*2N pattern 2N*2N;
Skip detection module, for detecting described J skipwhether be less than described J mergewith described J 2N*2N;
Skip and module is set, if for described J skipbe less than described J mergewith described J 2N*2N, then by described J skipbe set to candidate rate distortion costs J mode;
Second computing module, also for calculating the rate distortion costs J of described current prediction unit when adopting at least one intra prediction mode intra;
Final decision module, for from described J modewith J described at least one intrain select the final predictive mode of the minimum predictive mode of rate distortion costs as described current prediction unit.
7. device according to claim 6, is characterized in that, described device, also comprises:
3rd computing module, if also for described J skipbe not less than described J mergewith described J 2N*2N, then the rate distortion costs J of described current prediction unit when adopting interframe N*N pattern is calculated respectively n*N, adopt interframe 2N*N pattern time rate distortion costs J 2N*Nwith the rate distortion costs J adopted under interframe N*2N pattern n*2N;
First searches module, for from described J merge, described J 2N*2N, described J n*N, described J 2N*Nwith described J n*2Nin find out the first minimum value;
First arranges module, if be described J for described first minimum value merge, then by described J mergebe set to described candidate rate distortion costs J mode.
8. device according to claim 7, is characterized in that, described device, also comprises:
Enable detection module, if be not described J for described first minimum value merge, then the asymmetric predictive mode whether opening horizontal direction and/or vertical direction is detected;
4th computing module, if the asymmetric predictive mode for only opening horizontal direction, then calculates the rate distortion costs J of described current prediction unit when adopting interframe 2N*nU pattern respectively 2N*nU, adopt interframe 2N*nD pattern time rate distortion costs J 2N*nD;
Second searches module, for from described first minimum value, described J 2N*nUwith described J 2N*nDin find out the second minimum value;
5th computing module, if the asymmetric predictive mode for only opening vertical direction, then calculates the rate distortion costs J of described current prediction unit when adopting interframe nL*2N pattern respectively nL*2N, adopt interframe nR*2N pattern time rate distortion costs J nR*2N;
Described second searches module, also for from described first minimum value, described J nL*2Nwith described J nR*2Nin find out described second minimum value;
Second arranges module, for described second minimum value is set to described candidate rate distortion costs J mode.
9. device according to claim 7, is characterized in that, described device, also comprises:
Enable detection module, if be not described J for described first minimum value merge, then the asymmetric predictive mode whether described current prediction unit opens horizontal direction and/or vertical direction is detected;
6th computing module, if the asymmetric predictive mode for opening horizontal direction and vertical direction simultaneously, then calculates the rate distortion costs J of described current prediction unit when adopting interframe 2N*nU pattern respectively 2N*nU, adopt interframe 2N*nD pattern time rate distortion costs J 2N*nD, adopt interframe nL*2N pattern time rate distortion costs J nL*2N, adopt interframe nR*2N pattern time rate distortion costs J nR*2N;
Described 3rd searches module, for from described first minimum value, described J 2N*nU, described J 2N*nD, described J nL*2Nwith described J nR*2Nin find out the 3rd minimum value;
3rd arranges module, for described 3rd minimum value is set to described candidate rate distortion costs J mode.
10. according to the arbitrary described device of claim 6 to 9, it is characterized in that, described second computing module, specifically for calculating the rate distortion costs J of described current prediction unit when adopting 2N*2N pattern in frame respectively intra_2N*2N, rate distortion costs J when adopting N*N pattern in frame intra_N*N, rate distortion costs J when adopting PCM pattern in frame intra_ pCM.
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Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106534849A (en) * 2016-12-30 2017-03-22 杭州当虹科技有限公司 Fast HEVC interframe coding method
CN108632615A (en) * 2018-04-09 2018-10-09 首都师范大学 A method of the HEVC based on motion vector analysis judges SKIP patterns in advance
WO2018201954A1 (en) * 2017-05-03 2018-11-08 腾讯科技(深圳)有限公司 Processing method and device for video encoding, and storage medium
CN108924551A (en) * 2018-08-29 2018-11-30 腾讯科技(深圳)有限公司 The prediction technique and relevant device of video image coding pattern
CN110149512A (en) * 2018-09-14 2019-08-20 腾讯科技(深圳)有限公司 Inter-prediction accelerated method, control device, electronic device, computer storage medium and equipment
WO2020038357A1 (en) * 2018-08-20 2020-02-27 华为技术有限公司 Fusion candidate list construction method, device and encoding/decoding method and device
CN110855998A (en) * 2018-08-20 2020-02-28 华为技术有限公司 Fusion candidate list construction method and device, and encoding/decoding method and device
CN111277838A (en) * 2020-02-17 2020-06-12 腾讯科技(深圳)有限公司 Encoding mode selection method, device, electronic equipment and computer readable medium
CN111279699A (en) * 2019-04-26 2020-06-12 深圳市大疆创新科技有限公司 Video coding and decoding method and device
CN112118450A (en) * 2019-06-21 2020-12-22 杭州海康威视数字技术股份有限公司 Method and device for decoding and encoding prediction mode
WO2021238546A1 (en) * 2020-05-25 2021-12-02 腾讯科技(深圳)有限公司 Video encoding method, video playing back method, related devices and medium

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120082210A1 (en) * 2010-10-01 2012-04-05 Qualcomm Incorporated Coding prediction modes in video coding
CN103229507A (en) * 2010-11-25 2013-07-31 Lg电子株式会社 Method for signaling image information, and method for decoding image information using same
US20140241436A1 (en) * 2011-10-28 2014-08-28 Canon Kabushiki Kaisha Method and device for determining parameters for encoding or decoding of an image of a video sequence
CN104301739A (en) * 2013-07-18 2015-01-21 联发科技(新加坡)私人有限公司 Multi-view video coding method
CN104320656A (en) * 2014-10-30 2015-01-28 上海交通大学 Method for quickly selecting interframe encoding modes in x265 encoder
CN104333756A (en) * 2014-11-19 2015-02-04 西安电子科技大学 HEVC (High Efficiency Video Coding) prediction mode fast selection method based on time domain correlation

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120082210A1 (en) * 2010-10-01 2012-04-05 Qualcomm Incorporated Coding prediction modes in video coding
CN103155555A (en) * 2010-10-01 2013-06-12 高通股份有限公司 Coding prediction modes in video coding
CN103229507A (en) * 2010-11-25 2013-07-31 Lg电子株式会社 Method for signaling image information, and method for decoding image information using same
US20140241436A1 (en) * 2011-10-28 2014-08-28 Canon Kabushiki Kaisha Method and device for determining parameters for encoding or decoding of an image of a video sequence
CN104301739A (en) * 2013-07-18 2015-01-21 联发科技(新加坡)私人有限公司 Multi-view video coding method
CN104320656A (en) * 2014-10-30 2015-01-28 上海交通大学 Method for quickly selecting interframe encoding modes in x265 encoder
CN104333756A (en) * 2014-11-19 2015-02-04 西安电子科技大学 HEVC (High Efficiency Video Coding) prediction mode fast selection method based on time domain correlation

Cited By (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106534849A (en) * 2016-12-30 2017-03-22 杭州当虹科技有限公司 Fast HEVC interframe coding method
US10791326B2 (en) 2017-05-03 2020-09-29 Tencent Technology (Shenzhen) Company Limited Video coding processing method and apparatus, and storage medium
CN108810531A (en) * 2017-05-03 2018-11-13 腾讯科技(深圳)有限公司 Video coding processing method, device and electronic equipment
JP7026112B2 (en) 2017-05-03 2022-02-25 テンセント・テクノロジー・(シェンジェン)・カンパニー・リミテッド Video coding processing method, equipment, and storage medium
CN108810531B (en) * 2017-05-03 2019-11-19 腾讯科技(深圳)有限公司 Video coding processing method, device and electronic equipment
JP2019537904A (en) * 2017-05-03 2019-12-26 テンセント・テクノロジー・(シェンジェン)・カンパニー・リミテッド Video encoding method, apparatus, and storage medium
WO2018201954A1 (en) * 2017-05-03 2018-11-08 腾讯科技(深圳)有限公司 Processing method and device for video encoding, and storage medium
CN108632615A (en) * 2018-04-09 2018-10-09 首都师范大学 A method of the HEVC based on motion vector analysis judges SKIP patterns in advance
CN110855998B (en) * 2018-08-20 2023-04-11 华为技术有限公司 Fusion candidate list construction method and device, and fusion candidate list editing/decoding method and device
WO2020038357A1 (en) * 2018-08-20 2020-02-27 华为技术有限公司 Fusion candidate list construction method, device and encoding/decoding method and device
CN110855998A (en) * 2018-08-20 2020-02-28 华为技术有限公司 Fusion candidate list construction method and device, and encoding/decoding method and device
CN108924551B (en) * 2018-08-29 2022-01-07 腾讯科技(深圳)有限公司 Method for predicting video image coding mode and related equipment
CN108924551A (en) * 2018-08-29 2018-11-30 腾讯科技(深圳)有限公司 The prediction technique and relevant device of video image coding pattern
CN110149512A (en) * 2018-09-14 2019-08-20 腾讯科技(深圳)有限公司 Inter-prediction accelerated method, control device, electronic device, computer storage medium and equipment
CN110149512B (en) * 2018-09-14 2023-04-14 腾讯科技(深圳)有限公司 Inter-frame prediction acceleration method, device, computer storage medium and equipment
WO2020215338A1 (en) * 2019-04-26 2020-10-29 深圳市大疆创新科技有限公司 Video coding and decoding method and apparatus
CN111279699A (en) * 2019-04-26 2020-06-12 深圳市大疆创新科技有限公司 Video coding and decoding method and device
CN112118450A (en) * 2019-06-21 2020-12-22 杭州海康威视数字技术股份有限公司 Method and device for decoding and encoding prediction mode
CN112118450B (en) * 2019-06-21 2022-03-29 杭州海康威视数字技术股份有限公司 Method and device for decoding and encoding prediction mode
US12069249B2 (en) * 2020-02-17 2024-08-20 Tencent Technology (Shenzhen) Company Limited Coding mode selection method and apparatus, and electronic device and computer-readable medium
CN111277838A (en) * 2020-02-17 2020-06-12 腾讯科技(深圳)有限公司 Encoding mode selection method, device, electronic equipment and computer readable medium
WO2021164323A1 (en) * 2020-02-17 2021-08-26 腾讯科技(深圳)有限公司 Coding mode selection method and apparatus, and electronic device and computer readable medium
US20220191477A1 (en) * 2020-02-17 2022-06-16 Tencent Technology (Shenzhen) Company Limited Coding mode selection method and apparatus, and electronic device and computer-readable medium
WO2021238546A1 (en) * 2020-05-25 2021-12-02 腾讯科技(深圳)有限公司 Video encoding method, video playing back method, related devices and medium

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