CN1953561A - A system and method to correct white balance - Google Patents
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Abstract
The invention relates to a method for correcting white balance and relative system. Wherein, it recognizes target image or downloads the mixed light source of sampled image; based on the information of single light source of mixed light source, it obtains the correct parameter of mixed light source; based on the correct parameter, it corrects the target image to obtain the first image; based on the information of pixels of first image or downloaded sampled image, it obtains the correct parameter of each color component, and based on the correct parameter of each color component, it corrects and outputs the first image. The invention can obtain accurate white balance and the image with high quality.
Description
Technical field
The present invention relates to image processing field, relate in particular to a kind of method and system of correct white balance.
Background technology
At present, for image is carried out white balance correction, the bearing calibration of employing is:
Each component of the RGB of all picture elements divides other mean value in the statistical picture, wherein, the mean value of R component is Rmean, and the mean value of G component is Gmean, the mean value of B component is Bmean, asks for the correction parameter gr_gain of R component and the correction parameter gb_gain of B component more respectively:
gr_gain＝Gmean/Rmean
gb_gain＝Gmean/Bmean
Be reference with the G passage then, to R, the B passage is proofreaied and correct respectively, and promptly the RGB component value of each pixel carries out the RGB component value after following processing obtains this pixel correction:
R’＝R
*gr_gain
B’＝B
*gb_gian
G’＝G
Adopt above-mentioned bearing calibration, can carry out white balance correction, still,, mistake will occur for the situation that large stretch of color is arranged in the image to image.Its final result is that the large stretch of color in the image also is corrected into grey.Under some specific light source, the intensity of some color can very big (such as the R component), and under the very little situation of G component, calibration result is bad.And, because the complexity of light source (may comprise hybrid light source in the natural scene, new light sources (light source of not training), exceed the light source of training pattern reference color temperature etc.) and the complexity of scene content, make and to want by above-mentioned one step of bearing calibration well, unlikely realize white balance correction.And, if proofreading and correct, produces in this step than mistake, the color relation of the entire image after proofreading and correct so can occur than mistake.
Summary of the invention
The invention provides a kind of method and system of correct white balance, in order to obtain white balance more accurately.
In order to solve the problems of the technologies described above, the invention provides a kind of method of correct white balance, may further comprise the steps:
Discern the hybrid light source in pending image or its down-sampled images, obtain the correction parameter of described hybrid light source according to the information of each single light source in the described hybrid light source, and according to the correction parameter of described hybrid light source described pending image is proofreaied and correct and to be obtained first image;
Obtain the correction parameter of each color component according to the information of the picture element in described first image or its down-sampled images, and described first image is proofreaied and correct and exported according to the correction parameter of described each color component.
Further, said method also can have following characteristics: the information of described each single light source comprises the correction parameter of each single light source shared weight and described each single light source in described hybrid light source.
Further, said method also can have following characteristics: the correction parameter of described hybrid light source comprises the correction parameter of each color component of described hybrid light source, wherein, the correction parameter of each color component is the weighted sum of the correction parameter of corresponding color component in each single light source.
Further, said method also can have following characteristics: utilize the correction parameter of described hybrid light source that described pending image is carried out timing, utilize the correction parameter of each color component of described hybrid light source that the corresponding color component of picture element in the described pending image is proofreaied and correct respectively.
Further, said method also can have following characteristics: the correction parameter of described each single light source is obtained by training.
Further, said method also can have following characteristics: the acquisition methods of the weight of described each single light source is: obtain the model parameter of all picture elements in described pending image or its down-sampled images, and add up the quantity of the picture element in the model parameter scope of described each single light source respectively;
The weight of one of them single light source is a shared ratio in the sum of the picture element of quantity in the model parameter scope of described each single light source of the picture element in the model parameter scope of described single light source.
Further, said method also can have following characteristics: the model parameter scope of described each single light source is obtained by training.
Further, said method also can have following characteristics: the concrete grammar that obtains the correction parameter of each color component is: adding up the mean value of each color component of the picture element in described first image or its down-sampled images respectively, serves as with reference to the correction parameter that obtains described each color component with the mean value of one of them color component.
Further, said method also can have following characteristics: the correction parameter that obtains each color component according to the information that satisfies the picture element that imposes a condition in the picture element in described first image or its down-sampled images.
Further, said method also can have following characteristics: described imposing a condition is one of following three conditions or its combination in any:
Each color component value of described picture element is being in the respective color component preset threshold all;
The brightness of described picture element is in setting threshold;
The chrominance separation value of described picture element is in setting threshold.
Further, said method also can have following characteristics: when described impose a condition comprise described picture element brightness in setting threshold and/or the chrominance separation value of described picture element in setting threshold the time, the color space that described first image or its down-sampled images are transformed into brightness and chrominance separation obtains brightness in setting threshold and/or the picture element of chrominance separation value in setting threshold, keeps each color component value before the described conversion simultaneously;
Obtained satisfy the described picture element that imposes a condition after, the conversion before color space on carry out subsequent treatment.
Further, said method also can have following characteristics: when the quantity that satisfies the picture element impose a condition during greater than setting threshold, obtain the correction parameter of described each color component according to described first image or its down-sampled images, and described first image is proofreaied and correct according to the correction parameter of described each color component.
Further, said method also can have following characteristics: when the described quantity that satisfies the picture element impose a condition during greater than setting threshold, obtain and preserve the correction parameter of described each color component according to described first image or its down-sampled images;
When the described quantity that satisfies the picture element that imposes a condition is not more than setting threshold, described first image is proofreaied and correct according to the correction parameter of described each color component of preserving.
Further, said method also can have following characteristics: when the described quantity that satisfies the picture element that imposes a condition is not more than setting threshold, described first image is directly exported.
Further, said method also can have following characteristics: the picture element in colour of skin threshold value in described first image is directly exported.
The present invention also provides a kind of system of correct white balance, comprises first correction module and second correction module, wherein:
Described first correction module is discerned the hybrid light source in pending image or its down-sampled images, obtain the correction parameter of described hybrid light source according to the information of each single light source in the described hybrid light source, and according to the correction parameter of described hybrid light source described pending image is proofreaied and correct and to be obtained first image and output;
After described second correction module receives described first image, obtain the correction parameter of each color component according to the information of the picture element in described first image or its down-sampled images, and described first image is proofreaied and correct and exported according to the correction parameter of described each color component.
Further, said system also can have following characteristics: described second correction module comprises acquisition module, statistical module and processing module, wherein:
Described acquisition module obtains and satisfies the picture element that imposes a condition in first image of input or its down-sampled images, and exports to described statistical module;
Described statistical module is added up the described mean value that satisfies each color component of the picture element impose a condition respectively, serves as with reference to the correction parameter that obtains each color component and exports to described processing module with the mean value of one of them color component;
Described processing module is proofreaied and correct and is exported first image of input according to the correction parameter of described each color component.
Further, said system also can have following characteristics: described second correction module also comprises judge module, wherein:
Described acquisition module is exported to described statistical module and judge module respectively with satisfying the picture element that imposes a condition in first image or its down-sampled images;
Described judge module notifies described statistical module to handle when the described quantity that satisfies the picture element impose a condition during greater than setting threshold.
Further, said system also can have following characteristics: described processing module comprises memory cell and correcting unit, wherein:
Described statistical module is saved in described memory cell with the correction parameter of described each color component;
When described judge module is not more than setting threshold when the quantity of described picture element, notify described correcting unit;
Described correcting unit is proofreaied and correct and is exported first image of input according to the correction parameter of described each color component of preserving in the described memory cell after receiving the notice of described judge module.
Beneficial effect of the present invention is as follows:
Adopt technical solution of the present invention, can handle the situation of complicated hybrid light source well, and can adapt to the light source of new colour temperature, avoid the large stretch of bright-colored in the image is corrected into the situation of grey, obtain white balance more accurately, thereby obtain the better pictures quality.And technical solution of the present invention adopts two-stage to proofread and correct, and might when second-order correction image be recovered under first order correction has than the situation of mistake or under the situation of first order correction inefficacy.
Description of drawings
Fig. 1 is the flow chart that the first order is proofreaied and correct in the embodiment of the invention;
Fig. 2 is the flow chart of second-order correction in the embodiment of the invention;
Fig. 3 is the block diagram of the system of correct white balance in the embodiment of the invention.
Embodiment
Core concept of the present invention is: discern the hybrid light source in pending image or its down-sampled images, obtain the correction parameter of hybrid light source according to the information of each single light source in the hybrid light source, and according to the correction parameter of hybrid light source pending image is proofreaied and correct and to be obtained first image;
Obtain the correction parameter of each color component according to the information of the picture element in first image or its down-sampled images, and first image is proofreaied and correct and exported according to the correction parameter of each color component.
In embodiments of the present invention, carry out two-stage and proofread and correct, it is to adopt the method for light source classification and identification that image is tentatively proofreaied and correct that the first order is proofreaied and correct, and is equivalent to coarse adjustment; Second-order correction is to carry out meticulous adjusting on the basis that the first order is proofreaied and correct.Proofread and correct by two-stage, can obtain white balance and better pictures quality more accurately.
Below in conjunction with drawings and Examples the present invention is done description further.
The first order is proofreaied and correct:
In the present embodiment, what the first order was proofreaied and correct employing is the way of identification light source, and promptly discerning pending image is which kind of light source or which kind light source irradiation form, and comes the white balance of image is proofreaied and correct, the flow process that the first order is proofreaied and correct specifically may further comprise the steps as shown in Figure 1:
Step S101 is by model parameter scope and the correction parameter under each single light source of training acquisition;
In the present embodiment, corresponding cover correction parameter: gain_i_R, the gain_i_G of each single light source, gain_i_B, wherein, i represents to shine the i kind single light source of pending image;
Equally, the also corresponding model parameter scope of each single light source as long as the numerical value of the model parameter of the picture element in the pending image falls into the model parameter scope of certain single light source correspondence, represents that then this picture element is formed by this single light source irradiation.
When specific implementation, should be as much as possible and obtain model parameter scope and correction parameter under the single light source (for example: sunlight, fluorescent lamp, incandescent light, indoor light, outdoor light etc.) that may occur under the various scenes exactly, can better analyze like this, make that the result of first order correction in the present embodiment is more reasonable each single light source that shines pending image.
Step S102 obtains the model parameter of pending all picture elements of image;
Step S103 adds up the quantity counter_i of picture element in the model parameter scope that falls into each single light source in the pending image respectively;
As long as the picture element in the model parameter scope that falls into certain light source is arranged, just represents this light source that exists in this pending image.
Step S104 obtains each single light source weight factor weight_i separately that exists in this pending image;
In the hybrid light source scene, there are a plurality of single light sources, for example: existing daylight has fluorescent lamp again.The effect of this hybrid light source is exactly the weighted sum of a plurality of single light sources wherein.That is, each single light source all has contribution, and the degree of their contributions is exactly the size of weight.
In the present embodiment, there be N light source in this pending image, respectively sign fall into the quantity of the picture element in the model parameter scope of each single light source be counter_1, counter_2 ..., counter_N, then, in order to obtain this N single light source weight separately, can be earlier calculate picture element sum in the model parameter scope of each single light source by following formula:
sum_counter＝counter1+counter2+...counter_i+...+counterN (1)
Then the weight factor weight_i of i single light source is (normalized):
weigbt_i＝counter_i/sum_counter (2)
The i.e. ratio that accounts in i single light source weight sum for the picture element of quantity in the model parameter scope of each single light source of the interior picture element of the model parameter scope of this i single light source.
Step S105 obtains the correction parameter of each color component of hybrid light source;
The correction parameter of one of them color component of hybrid light source is exactly the weighted sum of the correction parameter of various these color components of light source;
In the present embodiment, the correction parameter of the R component of i kind light source is gain_i_R, and then the correction parameter of the R component of hybrid light source is exactly:
In like manner can calculate gain_B and gain_G, promptly can obtain the correction parameter of each color component of hybrid light source.
When specific implementation, pending image can be carried out down-sampling and obtain its down-sampled images, and discern hybrid light source in this down-sampled images, and utilize hybrid light source in this down-sampled images to obtain the correction parameter of hybrid light source, according to the correction parameter of this hybrid light source pending image is proofreaied and correct and obtained first image.So-called down-sampling is meant the process that picture size is diminished, and for example, the size of original image (width * height) is 640*480, and the size of the image behind the down-sampling is 320*240.Because down-sampling has just reduced size of images, but the profile of image and content do not change, statistical property is constant, therefore, can utilize hybrid light source in this down-sampled images to obtain the correction parameter of hybrid light source, correction parameter to the hybrid light source that obtains does not have big influence like this, but can greatly reduce the treating capacity of every statistics.
Step S106 utilizes the correction parameter of each color component of hybrid light source that pending image is proofreaied and correct and obtains first image.
Concrete bearing calibration is:
R’＝R
*gain_R
B’＝B
*gian_B
G’＝G
*gian_G
Promptly utilize the correction parameter of each color component of hybrid light source that the corresponding color component of the picture element in the pending image is proofreaied and correct respectively.
Second-order correction:
Second-order correction is to proofread and correct on first image that obtains in the first order to carry out.
In the present embodiment, the flow process of second-order correction specifically may further comprise the steps as shown in Figure 2:
Step S201 adds up the P that counts that satisfies the picture element that imposes a condition in first image;
In the present embodiment, above-mentioned imposing a condition is one of following three conditions or combination in any:
a、R’＜＝TH_R&&G’＜＝TH_G&&B’＜＝TH_B
The picture element that promptly satisfies condition should each color component value all less than being each color component preset threshold respectively, thereby exclude the occupy an leading position picture element of (i.e. this color supersaturation) of certain color, for example: bright-coloured picture element.
b、L＞＝Llow&&L＜＝Lhigh
The brightness of the picture element that promptly satisfies condition should be in setting threshold, thereby excludes too dark or too bright picture element.
c、Clow＜C＜Chigh
The chrominance separation value of the picture element that promptly satisfies condition should be in setting threshold, thereby excludes the too bright-coloured picture element of color.
TH_R, TH_G, TH_B, Llow, Lhigh, Clow, these threshold values of CHigh can be according to concrete needs setting.
In the present embodiment, only statistics meets the picture element that imposes a condition, and can make second-order correction can obtain white balance more accurately.
When this imposes a condition when comprising b and/or c, for the ease of obtaining the picture element of satisfy condition b and/or c, the color space that separates with colourity (C) to brightness (L) in first image transitions of RGB color space can be obtained the picture element of satisfy condition b and/or c, keep the preceding rgb value of conversion simultaneously, after getting access to the picture element that satisfies condition, on the RGB color space before the conversion, carry out subsequent treatment.
When specific implementation, also can add up the information of picture element all in first image, and carry out second-order correction according to the information of picture elements all in first image.
Whether step S202 judges the P that counts that satisfies the picture element that imposes a condition greater than setting threshold, if, carry out step S204, otherwise, carry out step S203;
When P＞TH_P (TH_P is a setting threshold), can think that statistics is believable, otherwise, think that statistics is insincere.It is more reasonable that processing can make the foundation of proofreading and correct like this, and the result is more credible in correction.
Step S203 utilizes the second-order correction parameter of each color component of preserving that first image is proofreaied and correct, and finishes;
For continuous images, the second-order correction parameter of each color component of its preservation is the second-order correction parameter of each color component of previous frame image, owing to be consecutive image, can think that then the image and the present frame difference of its previous frame are also little, can utilize the second-order correction parameter of each color component of previous frame image that present image is proofreaied and correct.
But, because in the present embodiment, the image of proofreading and correct may not be a consecutive image also, in this case, be not more than the setting threshold value if satisfy the P that counts of the picture element impose a condition, then can not proofread and correct and first image directly exported or carry out other processing this image.
Step S204 adds up the mean value that satisfies the RGB of the above-mentioned picture element that imposes a condition in first image;
The mean value of RGB is represented by Rmean ', Gmean ', Bmean ' respectively.
Step S205 is reference with the G component, calculates and preserve the second-order correction parameter of each color component;
With the G component is reference, calculates the second-order correction parameter gr_gain ' and the gb_gain ' of R, B component by following formula;
gr_gain’＝Gmean’/Rmean’ (4)
gr_gain’＝Gmean’/Bmean’ (5)
When specific implementation, also can adopt R or B component is reference, calculates the second-order correction parameter of other two color components.
Step S206 utilizes the second-order correction parameter that calculates that first image is carried out second-order correction.
R”＝R’
*gr_gain’ (6)
B”＝B’
*gr_gain’ (7)
G component as a reference then can be directly by G "=G '.
When specific implementation, can colour of skin point not carried out treatment for correcting.When needing colour of skin point not to be handled, can by judging whether picture element satisfies following condition and determine whether colour of skin point of this picture element:
gr_gain’＜＝TH_skin_gr&&gb_gain’＞＝TH_skin_gb (8)
TH_skin_gr and TH_skin_gb are two threshold values about the colour of skin, specifically can rule of thumb be worth setting.
If satisfy condition, think that then this picture element is a colour of skin point, when second-order correction, this picture element is not carried out second-order correction and first image is directly exported; Otherwise, think that this picture element is not a colour of skin point, carries out second-order correction with the second-order correction parameter to this picture element.
In second-order correction, can first image carry out down-sampling and obtain its down-sampled images, and utilize the down-sampled images of this first image to obtain the second-order correction parameter, thereby reduce the treating capacity of obtaining the second-order correction parameter in the second-order correction.
The system of the correct white balance in the one embodiment of the invention as shown in Figure 3, comprises first correction module 100 and second correction module 200, wherein:
Hybrid light source in first correction module, the 100 pending images of identification or its down-sampled images, obtain the correction parameter of hybrid light source according to the information of each single light source in the hybrid light source, and according to the correction parameter of hybrid light source pending image is proofreaied and correct and to be obtained first image and output;
After second correction module 200 receives first image, obtain the correction parameter of each color component, and first image is proofreaied and correct and exported according to the correction parameter of each color component according to the information of the picture element in first image or its down-sampled images.
This second correction module 200 comprises acquisition module 201, statistical module 203 and processing module 204, wherein:
When judge module 202 is not more than setting threshold when the quantity of picture element, notice correcting unit 206;
Correcting unit 206 is proofreaied and correct and is exported first image of input according to the correction parameter of each color component of preserving in the memory cell 205 after the notice that receives judge module 202.
Obviously, those skilled in the art can carry out various changes and modification to the present invention and not break away from the spirit and scope of the present invention.Like this, if of the present invention these are revised and modification belongs within the scope of claim of the present invention and equivalent technologies thereof, then the present invention also is intended to comprise these changes and modification interior.
Claims (19)
1, a kind of method of correct white balance is characterized in that, may further comprise the steps:
Discern the hybrid light source in pending image or its down-sampled images, obtain the correction parameter of described hybrid light source according to the information of each single light source in the described hybrid light source, and according to the correction parameter of described hybrid light source described pending image is proofreaied and correct and to be obtained first image;
Obtain the correction parameter of each color component according to the information of the picture element in described first image or its down-sampled images, and described first image is proofreaied and correct and exported according to the correction parameter of described each color component.
2, the method for claim 1 is characterized in that, the information of described each single light source comprises the correction parameter of each single light source shared weight and described each single light source in described hybrid light source.
3, method as claimed in claim 1 or 2, it is characterized in that, the correction parameter of described hybrid light source comprises the correction parameter of each color component of described hybrid light source, and wherein, the correction parameter of each color component is the weighted sum of the correction parameter of corresponding color component in each single light source.
4, method as claimed in claim 3, it is characterized in that, utilize the correction parameter of described hybrid light source that described pending image is carried out timing, utilize the correction parameter of each color component of described hybrid light source that the corresponding color component of picture element in the described pending image is proofreaied and correct respectively.
5, method as claimed in claim 2 is characterized in that, the correction parameter of described each single light source is obtained by training.
6, method as claimed in claim 2, it is characterized in that, the acquisition methods of the weight of described each single light source is: obtain the model parameter of all picture elements in described pending image or its down-sampled images, and add up the quantity of the picture element in the model parameter scope of described each single light source respectively;
The weight of one of them single light source is a shared ratio in the sum of the picture element of quantity in the model parameter scope of described each single light source of the picture element in the model parameter scope of described single light source.
7, method as claimed in claim 6 is characterized in that, the model parameter scope of described each single light source is obtained by training.
8, the method for claim 1, it is characterized in that, the concrete grammar that obtains the correction parameter of each color component is: adding up the mean value of each color component of the picture element in described first image or its down-sampled images respectively, serves as with reference to the correction parameter that obtains described each color component with the mean value of one of them color component.
9, as claim 1 or 8 described methods, it is characterized in that, obtain the correction parameter of each color component according to the information that satisfies the picture element that imposes a condition in the picture element in described first image or its down-sampled images.
10, method as claimed in claim 9 is characterized in that, described imposing a condition is one of following three conditions or its combination in any:
Each color component value of described picture element is being in the respective color component preset threshold all;
The brightness of described picture element is in setting threshold;
The chrominance separation value of described picture element is in setting threshold.
11, method as claimed in claim 10, it is characterized in that, when described impose a condition comprise described picture element brightness in setting threshold and/or the chrominance separation value of described picture element in setting threshold the time, the color space that described first image or its down-sampled images are transformed into brightness and chrominance separation obtains brightness in setting threshold and/or the picture element of chrominance separation value in setting threshold, keeps each color component value before the described conversion simultaneously;
Obtained satisfy the described picture element that imposes a condition after, the conversion before color space on carry out subsequent treatment.
12, method as claimed in claim 9, it is characterized in that, when the quantity that satisfies the picture element impose a condition during greater than setting threshold, obtain the correction parameter of described each color component according to described first image or its down-sampled images, and described first image is proofreaied and correct according to the correction parameter of described each color component.
13, method as claimed in claim 12 is characterized in that, when the described quantity that satisfies the picture element impose a condition during greater than setting threshold, obtains and preserve the correction parameter of described each color component according to described first image or its down-sampled images;
When the described quantity that satisfies the picture element that imposes a condition is not more than setting threshold, described first image is proofreaied and correct according to the correction parameter of described each color component of preserving.
14, method as claimed in claim 12 is characterized in that, when the described quantity that satisfies the picture element that imposes a condition is not more than setting threshold, described first image is directly exported.
15, the method for claim 1 is characterized in that, the picture element in colour of skin threshold value in described first image is directly exported.
16, a kind of system of correct white balance is characterized in that, comprises first correction module and second correction module, wherein:
Described first correction module is discerned the hybrid light source in pending image or its down-sampled images, obtain the correction parameter of described hybrid light source according to the information of each single light source in the described hybrid light source, and according to the correction parameter of described hybrid light source described pending image is proofreaied and correct and to be obtained first image and output;
After described second correction module receives described first image, obtain the correction parameter of each color component according to the information of the picture element in described first image or its down-sampled images, and described first image is proofreaied and correct and exported according to the correction parameter of described each color component.
17, system as claimed in claim 16 is characterized in that, described second correction module comprises acquisition module, statistical module and processing module, wherein:
Described acquisition module obtains and satisfies the picture element that imposes a condition in first image of input or its down-sampled images, and exports to described statistical module;
Described statistical module is added up the described mean value that satisfies each color component of the picture element impose a condition respectively, serves as with reference to the correction parameter that obtains each color component and exports to described processing module with the mean value of one of them color component;
Described processing module is proofreaied and correct and is exported first image of input according to the correction parameter of described each color component.
18, system as claimed in claim 17 is characterized in that, described second correction module also comprises judge module, wherein:
Described acquisition module is exported to described statistical module and judge module respectively with satisfying the picture element that imposes a condition in first image or its down-sampled images;
Described judge module notifies described statistical module to handle when the described quantity that satisfies the picture element impose a condition during greater than setting threshold.
19, system as claimed in claim 18 is characterized in that, described processing module comprises memory cell and correcting unit, wherein:
Described statistical module is saved in described memory cell with the correction parameter of described each color component;
When described judge module is not more than setting threshold when the quantity of described picture element, notify described correcting unit;
Described correcting unit is proofreaied and correct and is exported first image of input according to the correction parameter of described each color component of preserving in the described memory cell after receiving the notice of described judge module.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102300100A (en) * | 2010-06-28 | 2011-12-28 | 比亚迪股份有限公司 | White balance control device and method |
| CN102446347A (en) * | 2010-10-09 | 2012-05-09 | 株式会社理光 | White balance method and device for image |
| CN103227928A (en) * | 2013-03-29 | 2013-07-31 | 华为技术有限公司 | White balance adjusting method and device |
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