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CN102298769A - Colored fusion method of night vision low-light image and infrared image based on color transmission - Google Patents

Colored fusion method of night vision low-light image and infrared image based on color transmission Download PDF

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CN102298769A
CN102298769A CN2011101559584A CN201110155958A CN102298769A CN 102298769 A CN102298769 A CN 102298769A CN 2011101559584 A CN2011101559584 A CN 2011101559584A CN 201110155958 A CN201110155958 A CN 201110155958A CN 102298769 A CN102298769 A CN 102298769A
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image
component
color
average
night vision
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Inventor
金学波
鲍佳
杜晶晶
包晓敏
张水英
严国红
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Zhejiang University of Technology ZJUT
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Zhejiang University of Technology ZJUT
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Abstract

The present invention discloses the Color Fusion of a kind of the night vision low light image based on color transmitting and infrared image. The present invention will be seen that light and infrared image carry out linear fusion first, obtain grayscale fusion image
Figure 2011101559584100004DEST_PATH_IMAGE002
,
Figure 2011101559584100004DEST_PATH_IMAGE004
,
Figure 2011101559584100004DEST_PATH_IMAGE006
Component. Using the brightness and distribution of color of reference picture to grayscale fusion image
Figure 130480DEST_PATH_IMAGE002
,
Figure 166569DEST_PATH_IMAGE004
, It is adjusted, image data adjusted is gained into rgb space by yuv space contravariant and obtains final color fusion image, the blending image obtained using the method for the present invention is similar with color reference image Luminance Distribution, has good visual effect.

Description

Based on the night vision low light level image of color transmission and the Color Fusion of infrared image
Technical field
The invention belongs to image processing field, what relate to is a kind of visible images and infrared image fusion method based on color and brightness transmission.
Background technology
Infrared and visible light allos image co-registration can improve the target detection ability, can't detection feature when disclosing target and in single image, observing, important use value is arranged in fields such as security protection, driver assistances.Especially nighttime driving backup system, light image ground effectively processing can be expanded driver's visual range greatly, improve security.Improve the colouring information of image, fused images is shown as the natural color that is fit to eye-observation, can obviously improve the recognition performance of human eye, reduce operator's sense of fatigue.
Patent based on color notation conversion space has: unify method of adjustment (CN200810162135.2) based on the multi-level image of color transmission and disclose a kind of masstone coloured image based on the color transmission and unify method of adjustment, the image clarification method in foggy day (CN200810018174.5) that transmits based on self-adaption cluster color discloses a kind of image clarification method in foggy day that transmits based on self-adaption cluster color, but above-mentioned two kinds of methods only are applicable to single visible images.A kind ofly a kind of non-sampling Contourlet transfer pair gray scale visible images is proposed and infrared image decomposes based on the infrared of colour transmission and entropy information and color visible image fusion method (CN200810017443.6), employing is delivered in the fused images based on the colored transmission method of the l α β color space chromatic information with visible images, obtains the color integration image.Therefore this method need be utilized the color of visible light, is not suitable for the night vision low light level image under car bulb and the color integration of infrared image.
Summary of the invention
The present invention is directed to the deficiencies in the prior art, provide a kind of based on the night vision low light level image of color transmission and the Color Fusion of infrared image.
The step of the inventive method is as follows:
Step 1. is with reference picture TBe transformed into YUVThe space.
YUVThe space is another kind of color representation, YBe brightness, U, VBe the colourity of image, respectively expression blue and red with YDifference R-Y, B-Y, also claim colour difference signal.Utilize YUVThe space and RGBBetween transformational relation obtain reference picture T YUVThe space:
Figure 2011101559584100002DEST_PATH_IMAGE001
（1）
Step 2. night vision low light level image and infrared image fusion obtain fused images P
At first night vision low light level image is carried out monochromatization, obtain the gray-scale value of monochromatic visible light image
Figure 570173DEST_PATH_IMAGE002
Figure 2011101559584100002DEST_PATH_IMAGE003
（2）
In the formula
Figure 67538DEST_PATH_IMAGE004
, ,
Figure 145084DEST_PATH_IMAGE006
It is night vision low light level image R, G, BThe gray-scale value of component.Again with the gray-scale value of monochromatic visible light image
Figure 4456DEST_PATH_IMAGE002
Gray-scale value with infrared image
Figure 2011101559584100002DEST_PATH_IMAGE007
Merge and obtain fused images PPuppet Y, U, VComponent, method is:
Figure 737926DEST_PATH_IMAGE008
（3）
In the formula
Figure 2011101559584100002DEST_PATH_IMAGE009
,
Figure 973735DEST_PATH_IMAGE010
Be positive rational number, common span is
Figure 2011101559584100002DEST_PATH_IMAGE011
,
Figure 106120DEST_PATH_IMAGE012
,
Figure 2011101559584100002DEST_PATH_IMAGE013
Step 3. is according to reference picture T Y, U, VThe average of component and variance are adjusted fused images PPseudo- Y, U, VThe average and the variance of component (3) are delivered to fused images with the reference brightness distribution PIn, obtain the color integration image CSpecifically may further comprise the steps:
3-1. with fused images P Y, U, VComponent deducts its average respectively, eliminates the influence of background to transmission effect.
3-2. the image pixel value after handling is carried out convergent-divergent according to its ratio with the standard variance of reference picture, and adds the average of reference picture, that is:
Figure 198710DEST_PATH_IMAGE014
（4）
Figure 2011101559584100002DEST_PATH_IMAGE015
（5）
Figure 481793DEST_PATH_IMAGE016
（6）
Wherein
Figure 2011101559584100002DEST_PATH_IMAGE017
, ,
Figure 2011101559584100002DEST_PATH_IMAGE019
The expression fused images PEach pixel
Figure 373099DEST_PATH_IMAGE020
,
Figure 2011101559584100002DEST_PATH_IMAGE021
, Component.
Figure 2011101559584100002DEST_PATH_IMAGE023
,
Figure 344652DEST_PATH_IMAGE024
The expression reference picture The Y of T, U, VThe standard deviation of component and average.
Figure 2011101559584100002DEST_PATH_IMAGE025
,
Figure 653755DEST_PATH_IMAGE026
The expression fused images P Y, U, VThe standard deviation of component and average.
Figure 2011101559584100002DEST_PATH_IMAGE027
Be the proportional zoom coefficient, be used to regulate the brightness of fused image, span is usually , ,
Figure 2011101559584100002DEST_PATH_IMAGE031
Expression color integration image CEach pixel ,
Figure 384502DEST_PATH_IMAGE021
,
Figure 224282DEST_PATH_IMAGE022
Component.
Step 4. is passed through YUVInverse transformation obtains the color integration image C R, G, BValue, inverse transformation method:
Figure 704942DEST_PATH_IMAGE032
The invention has the beneficial effects as follows:
1. utilize and ask the image puppet Y, U, VThe method of component, with the chromatic information amount seldom night-viewing twilight image and the infrared image of black and white merge, set up the color contact between weak coloured image, black white image and the normal coloured image, provide necessary condition for weak coloured image, black white image carry out the colour enhancing.
2. according to reference picture Y, U, VEach component has carried out the color enhancement process to fused image, makes fused image have color component with the reference picture same distribution.
3. utilize
Figure 59700DEST_PATH_IMAGE027
The proportional zoom coefficient can adjust accordingly according to the brightness of actual conditions to fused images, has stronger adaptability.
Description of drawings
Fig. 1 is the inventive method process flow diagram.
Embodiment
The invention will be further described below in conjunction with accompanying drawing.
As shown in Figure 1, the inventive method may further comprise the steps:
Step (1) is with reference picture TBy RGBSpace conversion is YUVThe space obtains reference picture T Y, U, VThe space:
Figure 979115DEST_PATH_IMAGE001
Step (2) obtains fused images with the fusion of night vision low light level image and infrared image PPseudo- Y, U, VComponent, concrete grammar is: earlier night vision low light level image is carried out monochromatization, obtain the gray-scale value of monochromatic visible light image
Figure 673401DEST_PATH_IMAGE002
, the gray-scale value of monochromatic visible light image again
Figure 390209DEST_PATH_IMAGE002
Gray-scale value with infrared image
Figure 435525DEST_PATH_IMAGE007
Merge and obtain fused images PPuppet Y, U, VComponent, method is:
Figure 830734DEST_PATH_IMAGE003
Figure 441844DEST_PATH_IMAGE008
In the formula
Figure 529886DEST_PATH_IMAGE004
,
Figure 859236DEST_PATH_IMAGE005
,
Figure 58136DEST_PATH_IMAGE006
It is night vision low light level image R, G, BThe gray-scale value of component;
Figure 523753DEST_PATH_IMAGE009
,
Figure 782696DEST_PATH_IMAGE010
Be positive rational number, common span is ,
Figure 336354DEST_PATH_IMAGE012
,
Figure 859739DEST_PATH_IMAGE013
Step (3). regulate the color component of fused image according to reference picture, concrete grammar is: earlier with fused images PPuppet Y, U, VComponent deducts its average respectively, eliminates the influence of background to transmission effect; Again the image pixel value after handling is carried out convergent-divergent according to its ratio with the standard variance of reference picture, and add the average of reference picture, that is:
Figure 351900DEST_PATH_IMAGE014
Figure 327947DEST_PATH_IMAGE015
Wherein
Figure 574437DEST_PATH_IMAGE017
, , The expression fused images PEach pixel
Figure 779657DEST_PATH_IMAGE020
,
Figure 277634DEST_PATH_IMAGE021
,
Figure 843089DEST_PATH_IMAGE022
Component.
Figure 59307DEST_PATH_IMAGE023
,
Figure 4129DEST_PATH_IMAGE024
The expression reference picture The Y of T, U, VThe standard deviation of component and average.
Figure 356613DEST_PATH_IMAGE025
, The expression fused images P Y, U, VThe standard deviation of component and average.
Figure 799413DEST_PATH_IMAGE027
Be the proportional zoom coefficient, be used to regulate the brightness of fused image, span is usually
Figure 692599DEST_PATH_IMAGE029
,
Figure 602786DEST_PATH_IMAGE030
,
Figure 528017DEST_PATH_IMAGE031
Expression color integration image CEach pixel
Figure 814642DEST_PATH_IMAGE020
, ,
Figure 426069DEST_PATH_IMAGE022
Component.
Step (4). by YUVInverse transformation obtains the color integration image C R, G, BValue.Inverse transformation method:
Figure 900913DEST_PATH_IMAGE032
。

Claims (1)

1. based on the night vision low light level image of color transmission and the Color Fusion of infrared image, it is characterized in that the concrete steps of this method are:
Step 1. is with reference picture TBe transformed into YUVThe space, detailed process is:
Figure 2011101559584100001DEST_PATH_IMAGE002
（1）
Step 2. night vision low light level image and infrared image fusion obtain fused images P
At first night vision low light level image is carried out monochromatization, obtain the gray-scale value of monochromatic visible light image
Figure 2011101559584100001DEST_PATH_IMAGE004
Figure 2011101559584100001DEST_PATH_IMAGE006
（2）
In the formula ,
Figure 2011101559584100001DEST_PATH_IMAGE010
,
Figure 2011101559584100001DEST_PATH_IMAGE012
It is night vision low light level image R, G, BThe gray-scale value of component; Again with the gray-scale value of monochromatic visible light image
Figure 2321DEST_PATH_IMAGE004
Gray-scale value with infrared image
Figure 2011101559584100001DEST_PATH_IMAGE014
Merge and obtain fused images PPuppet Y, U, VComponent, detailed process is:
Figure 2011101559584100001DEST_PATH_IMAGE016
（3）
In the formula
Figure 2011101559584100001DEST_PATH_IMAGE018
,
Figure 2011101559584100001DEST_PATH_IMAGE020
Be positive rational number;
Step 3. is according to reference picture T Y, U, VThe average of component and variance are adjusted fused images PPseudo- Y, U, VThe average of component and variance are delivered to fused images with the reference brightness distribution PIn, obtain the color integration image CSpecifically may further comprise the steps:
3-1. with fused images P Y, U, VComponent deducts its average respectively, eliminates the influence of background to transmission effect;
3-2. the image pixel value after handling is carried out convergent-divergent according to its ratio with the standard variance of reference picture, and adds the average of reference picture, that is:
Figure 2011101559584100001DEST_PATH_IMAGE022
（4）
Figure 2011101559584100001DEST_PATH_IMAGE024
（5）
Figure 2011101559584100001DEST_PATH_IMAGE026
（6）
Wherein
Figure 2011101559584100001DEST_PATH_IMAGE028
,
Figure 2011101559584100001DEST_PATH_IMAGE030
,
Figure 2011101559584100001DEST_PATH_IMAGE032
Represent fused images respectively PEach pixel
Figure 2011101559584100001DEST_PATH_IMAGE034
,
Figure 2011101559584100001DEST_PATH_IMAGE036
,
Figure 2011101559584100001DEST_PATH_IMAGE038
Component;
Figure 2011101559584100001DEST_PATH_IMAGE040
,
Figure 2011101559584100001DEST_PATH_IMAGE042
Represent reference picture respectively The Y of T, U, VThe standard deviation of component and average;
Figure 2011101559584100001DEST_PATH_IMAGE044
,
Figure 2011101559584100001DEST_PATH_IMAGE046
Represent fused images respectively P Y, U, VThe standard deviation of component and average, Be the proportional zoom coefficient, be used to regulate the brightness of fused image;
Figure 2011101559584100001DEST_PATH_IMAGE050
,
Figure 2011101559584100001DEST_PATH_IMAGE052
, Expression color integration image CEach pixel ,
Figure 449276DEST_PATH_IMAGE036
,
Figure 349099DEST_PATH_IMAGE038
Component;
Step 4. is passed through YUVInverse transformation obtains the color integration image C R, G, BValue, the inverse transformation detailed process is:
Figure 2011101559584100001DEST_PATH_IMAGE056
。
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CN105046869A (en) * 2015-07-06 2015-11-11 北京理工大学 Forest fire prevention monitoring system based on double-wave-band fusion theory
CN105701765A (en) * 2015-09-23 2016-06-22 河南科技学院 Image-processing method and mobile terminal
CN105917641A (en) * 2013-08-01 2016-08-31 核心光电有限公司 Thin multi-aperture imaging system with auto-focus and methods for using same
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CN108040243A (en) * 2017-12-04 2018-05-15 南京航空航天大学 Multispectral 3-D visual endoscope device and image interfusion method
CN110211083A (en) * 2019-06-10 2019-09-06 北京宏大天成防务装备科技有限公司 A kind of image processing method and device
CN110651301A (en) * 2017-05-24 2020-01-03 黑拉有限责任两合公司 Method and system for automatically coloring night vision images
CN111402306A (en) * 2020-03-13 2020-07-10 中国人民解放军32801部队 Low-light-level/infrared image color fusion method and system based on deep learning
CN111476732A (en) * 2020-04-03 2020-07-31 江苏宇特光电科技股份有限公司 Image fusion and denoising method and system
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CN113362261A (en) * 2020-03-04 2021-09-07 杭州海康威视数字技术股份有限公司 Image fusion method

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Application publication date: 20111228