CN103491357B - A kind of auto white balance treatment method of image sensor - Google Patents
A kind of auto white balance treatment method of image sensor Download PDFInfo
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Abstract
The present invention discloses a kind of auto white balance treatment method of image sensor, mainly for providing a kind of white balancing treatment method adapting to the imageing sensor of various scene.The present invention, described method comprises: the quantity judging all greyscale color points on this image; If the quantity of greyscale color point is greater than first threshold, then greyscale color point methods is adopted to carry out white balance correction to image; If the quantity of greyscale color point is not more than first threshold, then the mean value of the gain factor that the gain factor adopting greyscale color point methods to obtain and gray world method obtain carries out white balance correction to image.The present invention promotes the white balance treatment effect of camera adaptive imageing sensor under various circumstances.
Description
Technical field
The present invention relates to technical field of image processing, be specifically related to a kind of white balancing treatment method of imageing sensor.
Background technology
Current security protection industry enters into the high definition epoch, and the cmos sensor adopting 1,000,000 grades has been trend.White balance (AWB, AutoWhitebalance) is a kind of process removing improper color.Human eye very naturally can adjust according to current color source colour temperature the object color seen, and camera apparatus is often difficult to realize perfect Automatic white balance.Just because of transducer does not have the color constancy under the different light colour temperature of human eye, with regard to needing, human eye be it seems that the object of white carries out the reduction of color by white balance module, make it on photo, also be rendered as white.
Traditional white balance algorithm designs based on the method for the white point found in environment, although most of scene can be suitable for, but when having and not possessing white point in reflective, environment by force, image can not realize white balance function, thus image there will be colour cast, thus have impact on the use of HD video.
Summary of the invention
For the problems referred to above, the invention provides one and improve colour cast phenomenon, promote the white balancing treatment method of camera adaptive imageing sensor under various circumstances.
For achieving the above object, auto white balance treatment method of image sensor of the present invention, described method comprises: the colour of all pixels in computed image, judge the quantity of all greyscale color points on this image, if the quantity of greyscale color point is greater than first threshold, then greyscale color point methods is adopted to carry out white balance correction to image;
If the quantity of greyscale color point is not more than first threshold, then the mean value of the gain factor that the gain factor adopting greyscale color point methods to obtain and gray world method obtain carries out white balance correction to image.
Further, judge that the computational methods of the quantity of all greyscale color points on image comprise: the chromatic value of computed image pixel and the absolute value of brightness value ratio and whether be greater than Second Threshold T, computing formula is as follows:
If F < is T, then this pixel is greyscale color point; If F >=T, then this pixel is not greyscale color point.
Further, described greyscale color point method is carried out white balance process to image and is specifically comprised:
The three primary color components average R separately of pixel in difference computed image
avg, G
avg, B
avg;
Average based on described three primary color components obtains the gain factor of each primary components, and the computing formula of described gain factor is as follows:
Rgw_gain＝G
avg/R
avg；
Ggw_gain＝G
avg/G
avg；
Bgw_gain＝G
avg/B
avg；
Wherein, Rgw_gain is the gain factor of red color component;
Ggw_gain is the gain factor of green color component;
Bgw_gain is the gain factor of blue color component;
Colour after correcting based on each color component of described gain factor computed image, makes R, G, B component of image be multiplied with corresponding gain factor respectively, obtains image after white balance process, corrects formula as follows:
R_awb＝Rgw_gain*R；
G_awb＝Ggw_gain*G；
B_awb＝Bgw_gain*B；
Wherein, R_awb is the colour after red color component is corrected;
G_awb is the colour after green color component is corrected;
B_awb is the colour after blue color component is corrected.
Further, the mean value of the gain factor that described greyscale color point methods obtains and the gain factor that gray world method obtains comprises the concrete grammar that image carries out white balance correction:
The three-component average R separately of the color of image of whole pixel in computed image
avg, G
avg, B
avg;
Choose the gray pixels point in image, calculate the color of image three-component average R of described gray pixels point respectively
Ω, G
Ω, B
Ω;
Average based on the color component of whole pixel obtains the red color of greyscale color method and gain factor Rgw_gain, Bgw_gain of blue color component and obtains the red color of gray world method and gain factor Rgr_gain, Bgr_gain of blue color component based on the average of the color component of whole gray pixels point, and computing formula is as follows:
Rgw_gain＝G
avg/R
avg；
Bgw_gain＝G
avg/B
avg；
Rgr_gain＝G
Ω/R
Ω；
Bgr_gain＝G
Ω/B
Ω；
Calculate the mean value of the gain factor of each color component of described greyscale color method and gray world method, obtain the gain factor of final color component, computing formula is as follows:
Rfinal_gain＝avg(Rgw_gain，Rgr_gain)；
Bfinal_gain＝avg(Bgw_gain，Bgr_gain)；
Wherein, Rfinal_gain is the gain factor of final red color component;
Bfinal_gain is the gain factor of final blue color component;
Colour after correcting based on red, the blue color component of the gain factor computed image of described final color component, makes R, B component of image be multiplied with the gain factor of corresponding final color component respectively, obtains image after white balance process, corrects formula as follows:
R_awb＝Rfinal_gain*R；
B_awb＝Bfinal_gain*B；
Wherein, R_awb is the colour after red color component is corrected;
B_awb is the colour after blue color component is corrected.
Auto white balance treatment method of image sensor of the present invention, combine the advantage that gray world method is simple and quick and the deviation of gray world method when ash point is a lot of is little, avoid large monochromatic block object when existing, but when image scene color is not enriched, there is larger deviation in gray world method, if the gray scale of image is not seldom or when having an ash point, and the defect of larger deviation is there will be based on greyscale color point method, improve camera greatly under different-colour environment, color rendition under different scene, make high-definition image color more bright-coloured, correctly.
Accompanying drawing explanation
Fig. 1 is the flow chart of auto white balance treatment method of image sensor of the present invention.
Embodiment
Below in conjunction with Figure of description, the present invention will be further described.
Found by large quantitative statistics, a natural scene often includes a large amount of greyscale color points, as the shadow of object.Gray color point alleged by us refers to the point that RGB component is equal, and its value is designated as R, G, B.Under standard sources illuminate condition, greyscale color point is rendered as very pure grey.Under non-standard colour temperature is irradiated, can there is different skews along with the difference of light source color temperature in these Grey Point colors, partially red under low colour temperature, partially blue under high color temperature.What greyscale color point represented entire image due to small color that light source irradiation causes departs from program, can be used for accurate estimated color temperature.
As shown in Figure 1, the present embodiment auto white balance treatment method of image sensor, described method comprises: the colour of all pixels in computed image, judge the quantity of all greyscale color points on this image, if the quantity of greyscale color point is greater than first threshold, then greyscale color point methods is adopted to carry out white balance correction to image;
If the quantity of greyscale color point is not more than first threshold, then the mean value of the gain factor that the gain factor adopting greyscale color point methods to obtain and gray world method obtain carries out white balance correction to image.
Further, in the present embodiment, judge that the computational methods of the quantity of all greyscale color points on image comprise: the chromatic value of computed image pixel and the absolute value of brightness value ratio and whether be greater than Second Threshold T, computing formula is as follows:
If F < is T, then this pixel is greyscale color point;
If F >=T, then this pixel is not greyscale color point.
Further, in the present embodiment, described greyscale color point method is carried out white balance process to image and is specifically comprised:
The three primary color components average R separately of pixel in difference computed image
avg, G
avg, B
avg; Average based on described three primary color components obtains the gain factor of each primary components, and the computing formula of described gain factor is as follows:
Rgw_gain＝G
avg/R
avg；
Ggw_gain＝G
avg/G
avg；
Bgw_gain＝G
avg/B
avg；
Wherein, Rgw_gain is the gain factor of red color component;
Ggw_gain is the gain factor of green color component;
Bgw_gain is the gain factor of blue color component;
Colour after correcting based on each color component of described gain factor computed image, makes R, G, B component of image be multiplied with corresponding gain factor respectively, obtains image after white balance process, corrects formula as follows:
R_awb＝Rgw_gain*R；
G_awb＝Ggw_gain*G；
B_awb＝Bgw_gain*B；
Wherein, R_awb is the colour after red color component is corrected;
G_awb is the colour after green color component is corrected;
B_awb is the colour after blue color component is corrected.
Further, in the present embodiment, the mean value of the gain factor that described greyscale color point methods obtains and the gain factor that gray world method obtains comprises the concrete grammar that image carries out white balance correction:
The three-component average R separately of the color of image of whole pixel in computed image
avg, G
avg, B
avg; Choose the gray pixels point in image, calculate the color of image three-component average R of described gray pixels point respectively
Ω, G
Ω, B
Ω;
Average based on the color component of whole pixel obtains the red color of greyscale color method and gain factor Rgw_gain, Bgw_gain of blue color component and obtains the red color of gray world method and gain factor Rgr_gain, Bgr_gain of blue color component based on the average of the color component of whole gray pixels point, and computing formula is as follows:
Rgw_gain＝G
avg/R
avg；
Bgw_gain＝G
avg/B
avg；
Rgr_gain＝G
Ω/R
Ω；
Bgr_gain＝G
Ω/B
Ω；
Calculate the mean value of the gain factor of each color component of described greyscale color method and gray world method, obtain the gain factor of final color component, computing formula is as follows:
Rfinal_gain＝avg(Rgw_gain，Rgr_gain)；
Bfinal_gain＝avg(Bgw_gain，Bgr_gain)；
Wherein, Rfinal_gain is the gain factor of final red color component;
Bfinal_gain is the gain factor of final blue color component;
Colour after correcting based on red, the blue color component of the gain factor computed image of described final color component, makes R, B component of image be multiplied with the gain factor of corresponding final color component respectively, obtains image after white balance process, corrects formula as follows:
R_awb＝Rfinal_gain*R；
B_awb＝Bfinal_gain*B；
Wherein, R_awb is the colour after red color component is corrected;
B_awb is the colour after blue color component is corrected.
Wherein Second Threshold, this value is drawn by a large amount of experiments, is generally 1/20 of all pixels of image.Auto white balance treatment method of image sensor of the present invention, combine the advantage that gray world method is simple and quick and the deviation of gray world method when ash point is a lot of is little, avoid large monochromatic block object when existing, but when image scene color is not enriched, there is larger deviation in gray world method, if the gray scale of image is not seldom or when having an ash point, and the defect of larger deviation is there will be based on greyscale color point method, improve camera greatly under different-colour environment, color rendition under different scene, make high-definition image color more bright-coloured, correctly.
Above; be only preferred embodiment of the present invention, but protection scope of the present invention is not limited thereto, is anyly familiar with those skilled in the art in the technical scope that the present invention discloses; the change that can expect easily or replacement, all should be encompassed within protection scope of the present invention.Therefore, the protection range that protection scope of the present invention should define with claim is as the criterion.
Claims (2)
1. an auto white balance treatment method of image sensor, is characterized in that, described method comprises:
The colour of all pixels in computed image, judges the quantity of all greyscale color points on this image,
If the quantity of greyscale color point is greater than first threshold, then greyscale color point methods is adopted to carry out white balance correction to image; Described greyscale color point method is carried out white balance process to image and is specifically comprised:
The three primary color components average R separately of pixel in difference computed image
avg, G
avg, B
avg;
Average based on described three primary color components obtains the gain factor of each primary components, and the computing formula of described gain factor is as follows:
Rgw_gain=G
avg/R
avg;
Ggw_gain=G
avg/G
avg;
Bgw_gain=G
avg/B
avg;
Wherein, Rgw_gain is the gain factor of red color component;
Ggw_gain is the gain factor of green color component;
Bgw_gain is the gain factor of blue color component;
Colour after correcting based on each color component of described gain factor computed image, makes R, G, B component of image be multiplied with corresponding gain factor respectively, obtains image after white balance process, corrects formula as follows:
R_awb=Rgw_gain*R;
G_awb=Ggw_gain*G;
B_awb=Bgw_gain*B;
Wherein, R_awb is the colour after red color component is corrected;
G_awb is the colour after green color component is corrected;
B_awb is the colour after blue color component is corrected;
If the quantity of greyscale color point is not more than first threshold, then the mean value of the gain factor that the gain factor adopting greyscale color point methods to obtain and gray world method obtain carries out white balance correction to image; The mean value of the gain factor that described greyscale color point methods obtains and the gain factor that gray world method obtains comprises the concrete grammar that image carries out white balance correction:
The three-component average R separately of the color of image of whole pixel in computed image
avg, G
avg, B
avg;
Choose the gray pixels point in image, calculate the color of image three-component average R of described gray pixels point respectively
Ω, G
Ω, B
Ω;
Average based on the color component of whole pixel obtains the red color of greyscale color method and gain factor Rgw_gain, Bgw_gain of blue color component and obtains the red color of gray world method and gain factor Rgr_gain, Bgr_gain of blue color component based on the average of the color component of whole gray pixels point, and computing formula is as follows:
Rgw_gain=G
avg/R
avg;
Bgw_gain=G
avg/B
avg;
Rgr_gain=G
Ω/R
Ω;
Bgr_gain=G
Ω/B
Ω;
Calculate the mean value of the gain factor of each color component of described greyscale color method and gray world method, obtain the gain factor of final color component, computing formula is as follows:
Rfinal_gain=avg（Rgw_gain，Rgr_gain）；
Bfinal_gain=avg（Bgw_gain，Bgr_gain）；
Wherein, Rfinal_gain is the gain factor of final red color component;
Bfinal_gain is the gain factor of final blue color component;
Colour after correcting based on red, the blue color component of the gain factor computed image of described final color component, makes R, B component of image be multiplied with the gain factor of corresponding final color component respectively, obtains image after white balance process, corrects formula as follows:
R_awb=Rfinal_gain*R;
B_awb=Bfinal_gain*B;
Wherein, R_awb is the colour after red color component is corrected;
B_awb is the colour after blue color component is corrected.
2. a kind of auto white balance treatment method of image sensor according to claim 1, is characterized in that, judges that the computational methods of the quantity of all greyscale color points on image comprise:
The chromatic value of computed image pixel and the absolute value of brightness value ratio and whether be greater than Second Threshold T, computing formula is as follows:
If F < is T, then this pixel is greyscale color point;
If F >=T, then this pixel is not greyscale color point.
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| CN103974053B (en) * | 2014-05-12 | 2016-04-13 | 华中科技大学 | A kind of Automatic white balance antidote extracted based on ash point |
| CN105828058B (en) * | 2015-05-29 | 2019-02-15 | 维沃移动通信有限公司 | A kind of method of adjustment and device of white balance |
| CN104954772B (en) * | 2015-06-26 | 2017-05-10 | 济南中维世纪科技有限公司 | Image adjacent-grey pixel selection algorithm applied to automatic white balance algorithm |
| CN107404640B (en) * | 2016-05-20 | 2018-12-25 | 北京集创北方科技股份有限公司 | The white balance correcting and digital imaging device of digital imaging device |
| CN106303473B (en) * | 2016-08-23 | 2019-01-29 | 宁波江丰生物信息技术有限公司 | A kind of white balance adjusting method and camera |
| CN108205671A (en) * | 2016-12-16 | 2018-06-26 | 浙江宇视科技有限公司 | Image processing method and device |
| CN107027017A (en) * | 2017-04-25 | 2017-08-08 | 建荣半导体（深圳）有限公司 | A kind of method of adjustment, device, picture processing chip and the storage device of image white balance |
| CN109151426B (en) * | 2017-06-28 | 2020-05-22 | 杭州海康威视数字技术股份有限公司 | White balance adjusting method and device, camera and medium |
| CN107920242B (en) * | 2017-12-28 | 2019-08-16 | 努比亚技术有限公司 | A kind of optimization method of automatic white balance, terminal and computer readable storage medium |
| CN108093234B (en) * | 2017-12-29 | 2019-10-29 | 努比亚技术有限公司 | A kind of image processing method, terminal and storage medium |
| CN109561292A (en) * | 2018-12-26 | 2019-04-02 | 凌云光技术集团有限责任公司 | A kind of white balancing treatment method and device for camera system |
| CN110505459B (en) * | 2019-08-16 | 2020-12-11 | 域鑫科技（惠州）有限公司 | Image color correction method, device and storage medium suitable for endoscope |
| CN112204957A (en) * | 2019-09-20 | 2021-01-08 | 深圳市大疆创新科技有限公司 | White balance processing method and device, movable platform and camera |
| CN110794599B (en) * | 2019-10-23 | 2021-11-16 | 联想(北京)有限公司 | Color cast detection method, electronic equipment and computer readable storage medium |
| CN112950635A (en) * | 2021-04-26 | 2021-06-11 | Oppo广东移动通信有限公司 | Gray dot detection method, gray dot detection device, electronic device, and storage medium |
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