CN103491357A - Auto white balance treatment method of image sensor - Google Patents
Auto white balance treatment method of image sensor Download PDFInfo
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Abstract
The invention discloses an auto white balance treatment method of an image sensor, and mainly aims at providing an auto white balance treatment method of an image sensor which is applicable to various scenes. The method comprises the following steps of judging the number of gray scale color spots on an image; if the number of the gray scale color spots is greater than a first threshold, carrying out white balance correction on the image by using a gray scale color sport method; if the number of the gray scale color spots is not greater than the first threshold, carrying out white balance correction on the image by using an average value of a gray scale color sport method gain factor and a gray scale world method gain factor. Due to adoption of the method, the white balance treatment effect of the image sensor of a camera with adaptation to different environments is improved.
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 that adopts 1,000,000 grades has been trend.White balance (AWB, Auto White balance) is a kind of process of removing improper color.Human eye can be very natural adjust according to current color source colour temperature the object color of seeing, and camera apparatus often is difficult to realize perfect Automatic white balance.White balance (AWB, Auto White balance) is a kind of process of removing improper color.Human eye can be very natural adjust according to current color source colour temperature the object color of seeing, and camera apparatus often is 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, white balance module just need to be it seems human eye that white object carries out the reduction of color, makes it also be rendered as white on photo.
Just because of transducer does not have the color constancy under the different light colour temperature of human eye, white balance module just need to be it seems human eye that white object carries out the reduction of color, makes it also be rendered as white on photo.The method of traditional white balance algorithm based on finding the white point in environment designs, although most of scene can be suitable for, but when in reflective, environment is arranged by force, not possessing white point, image can not be realized white balance function, thereby image there will be colour cast, thereby affected the use of HD video.
Summary of the invention
For the problems referred to above, the invention provides a kind of colour cast phenomenon of improving, promote the white balancing treatment method of the adaptive imageing sensor of camera under varying environment.
For achieving the above object; imageing sensor white balancing treatment method of the present invention; described method comprises: the colour of all pixels on computed image; judge the quantity of this above greyscale color point of image; if the quantity of greyscale color point is greater than first threshold, adopt the greyscale color point methods to carry out the white balance rectification to image;
If the quantity of greyscale color point is not more than first threshold, adopt the mean value of greyscale color point methods gain factor and gray scale world method gain factor to carry out the white balance rectification to image.
Further, the computational methods of described image ash point quantity comprise: the thoroughly deserving and whether be greater than Second Threshold T with the ratio of brightness value of the chromatic value of computed image pixel, and wherein said computing formula is as follows:
If F<T, this pixel is the greyscale color point; If F >=T, this pixel is not the greyscale color point.
Further, described greyscale color point method is carried out the white balance processing to image and is specifically comprised:
The three primary color components average A separately of pixel in the difference computed image
vg, A
vg, A
vg;
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?=?Gavg?/?Ravg?;
Ggw_gain?=?Gavg?/?Gavg;
Bgw_gain?=?Gavg?/?Bavg;
Wherein, the gain factor that Rgw_gain is the red color component;
The gain factor that Ggw_gain is green color component;
The gain factor that Bgw_gain is blue color component;
Colour after correcting based on each color component of described gain factor computed image, make R, the G of image, B component multiply each other with corresponding gain factor respectively, obtains white balance and process rear image, and described rectification formula is as follows:
R_awb?=?Rgw_gain?*?R?;
G_awb?=?Ggw_gain?*?G?;
B_awb?=?Bgw_gain?*?B?;
Wherein, R_awb is the colour after the 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 concrete grammar that the mean value of described greyscale color point method gain factor and gray scale world gain factor carries out the white balance rectification to image comprises:
The three-component average R separately of the color of image of whole pixels in computed image
avg, G
avg, B
avg;
Choose the gray pixels point in image, calculate respectively the color of image three-component average R of described gray pixels point
Ω, G
Ω, B
Ω;
The average of the color component based on whole pixels obtains the red color of greyscale color method and gain factor Rgw_gain, the Bgw_gain of blue color component and the average of the color component based on whole gray-scale pixels points and obtains gain factor Rgr_gain, the Bgr_gain that the greyscale color method obtains red color and blue color component, and described computing formula is as follows:
Rgw_gain?=?Gavg?/?Ravg?;
Bgw_gain?=?Gavg?/?Bavg;
Rgr_gain?=?G
Ω?/?R
Ω;
Bgr_gain?=?
The accompanying drawing explanation
Fig. 1 is the flow chart of imageing sensor white balancing treatment method of the present invention.
Embodiment
Below in conjunction with Figure of description, the present invention will be further described.
By large quantitative statistics, find, a natural scene often includes a large amount of greyscale color points, as the shadow of object.We refer to the point that the RGB component is equal at alleged grey color dot, and its value is designated as R, G, B.Under the standard sources illuminate condition, the greyscale color point is rendered as very pure grey.Under non-standard colour temperature is irradiated, different skews can occur 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.The small color that greyscale color point causes due to light source irradiation has represented the program that departs from of entire image, can be used for accurate estimated color temperature.
As shown in Figure 1; the present embodiment imageing sensor white balancing treatment method; described method comprises: the colour of all pixels on computed image; judge the quantity of this above greyscale color point of image; if the quantity of greyscale color point is greater than first threshold, adopt the greyscale color point methods to carry out the white balance rectification to image;
If the quantity of greyscale color point is not more than first threshold, adopt the mean value of greyscale color point methods gain factor and gray scale world method gain factor to carry out the white balance rectification to image.
Further, in the present embodiment, the computational methods of described image ash point quantity comprise: the thoroughly deserving and whether be greater than Second Threshold T with the ratio of brightness value of the chromatic value of computed image pixel, and wherein said computing formula is as follows:
If F<T, this pixel is the greyscale color point;
If F >=T, this pixel is not the greyscale color point.
Further, in the present embodiment, described greyscale color point method is carried out the white balance processing to image and is specifically comprised:
The three primary color components average A separately of pixel in the difference computed image
vg, A
vg, A
vg;
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?=?Gavg?/?Ravg?;
Ggw_gain?=?Gavg?/?Gavg;
Bgw_gain?=?Gavg?/?Bavg;
Wherein, the gain factor that Rgw_gain is the red color component;
The gain factor that Ggw_gain is green color component;
The gain factor that Bgw_gain is blue color component;
Colour after correcting based on each color component of described gain factor computed image, make R, the G of image, B component multiply each other with corresponding gain factor respectively, obtains white balance and process rear image, and described rectification formula is as follows:
R_awb?=?Rgw_gain?*?R?;
G_awb?=?Ggw_gain?*?G?;
B_awb?=?Bgw_gain?*?B?;
Wherein, R_awb is the colour after the 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 concrete grammar that the mean value of described greyscale color point method gain factor and gray scale world gain factor carries out the white balance rectification to image comprises:
The three-component average R separately of the color of image of whole pixels in computed image
avg, G
avg, B
avg; Choose the gray pixels point in image, calculate respectively the color of image three-component average R of described gray pixels point
Ω, G
Ω, B
Ω;
The average of the color component based on whole pixels obtains the red color of greyscale color method and gain factor Rgw_gain, the Bgw_gain of blue color component and the average of the color component based on whole gray-scale pixels points and obtains gain factor Rgr_gain, the Bgr_gain that the greyscale color method obtains red color and blue color component, and described computing formula is as follows:
Rgw_gain?=?Gavg?/?Ravg?;
Bgw_gain?=?Gavg?/?Bavg;
Rgr_gain?=?G
Ω?/?R
Ω;
Bgr_gain?=?
Above; be only preferred embodiment of the present invention, but protection scope of the present invention is not limited to this, anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range that claim was defined.
Claims (4)
1. an imageing sensor white balancing treatment method, is characterized in that, described method comprises:
The colour of all pixels on computed image, judge the quantity of this above greyscale color point of image,
If the quantity of greyscale color point is greater than first threshold, adopt the greyscale color point methods to carry out the white balance rectification to image;
If the quantity of greyscale color point is not more than first threshold, adopt the mean value of greyscale color point methods gain factor and gray scale world method gain factor to carry out the white balance rectification to image.
2. a kind of imageing sensor white balancing treatment method according to claim 1, is characterized in that, the computational methods of described image ash point quantity comprise:
The thoroughly deserving and whether be greater than Second Threshold T with the ratio of brightness value of the chromatic value of computed image pixel, wherein said computing formula is as follows:
If F<T, this pixel is the greyscale color point;
If F >=T, this pixel is not the greyscale color point.
3. a kind of imageing sensor white balancing treatment method according to claim 1, is characterized in that, described greyscale color point method is carried out the white balance processing to image and specifically comprised:
The three primary color components average A separately of pixel in the difference computed image
vg, A
vg, A
vg;
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?=?Gavg?/?Ravg?;
Ggw_gain?=?Gavg?/?Gavg;
Bgw_gain?=?Gavg?/?Bavg;
Wherein, the gain factor that Rgw_gain is the red color component;
The gain factor that Ggw_gain is green color component;
The gain factor that Bgw_gain is blue color component;
Colour after correcting based on each color component of described gain factor computed image, make R, the G of image, B component multiply each other with corresponding gain factor respectively, obtains white balance and process rear image, and described rectification formula is as follows:
R_awb?=?Rgw_gain?*?R?;
G_awb?=?Ggw_gain?*?G?;
B_awb?=?Bgw_gain?*?B?;
Wherein, R_awb is the colour after the 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.
4. a kind of imageing sensor white balancing treatment method according to claim 1, it is characterized in that: the concrete grammar that the mean value of described greyscale color point method gain factor and gray scale world gain factor carries out the white balance rectification to image comprises:
The three-component average R separately of the color of image of whole pixels in computed image
avg, G
avg, B
avg;
Choose the gray pixels point in image, calculate respectively the color of image three-component average R of described gray pixels point
Ω, G
Ω, B
Ω;
The average of the color component based on whole pixels obtains the red color of greyscale color method and gain factor Rgw_gain, the Bgw_gain of blue color component and the average of the color component based on whole gray-scale pixels points and obtains gain factor Rgr_gain, the Bgr_gain that the greyscale color method obtains red color and blue color component, and described computing formula is as follows:
Rgw_gain?=?Gavg?/?Ravg?;
Bgw_gain?=?Gavg?/?Bavg;
Rgr_gain?=?GΩ?/?RΩ;
Bgr_gain?=?
。
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Cited By (15)
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| CN103974053A (en) * | 2014-05-12 | 2014-08-06 | 华中科技大学 | Automatic white balance correction method based on grey dot extraction |
| CN104954772A (en) * | 2015-06-26 | 2015-09-30 | 济南中维世纪科技有限公司 | Image adjacent-grey pixel selection algorithm applied to automatic white balance algorithm |
| CN105828058A (en) * | 2015-05-29 | 2016-08-03 | 维沃移动通信有限公司 | Adjustment method and device of white balance |
| CN106303473A (en) * | 2016-08-23 | 2017-01-04 | 宁波江丰生物信息技术有限公司 | A kind of white balance adjusting method and camera |
| 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 |
| CN107404640A (en) * | 2016-05-20 | 2017-11-28 | 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 |
| CN107920242A (en) * | 2017-12-28 | 2018-04-17 | 努比亚技术有限公司 | A kind of optimization method of automatic white balance, terminal and computer-readable recording medium |
| CN108093234A (en) * | 2017-12-29 | 2018-05-29 | 努比亚技术有限公司 | A kind of image processing method, terminal and storage medium |
| CN108205671A (en) * | 2016-12-16 | 2018-06-26 | 浙江宇视科技有限公司 | Image processing method and device |
| WO2019001163A1 (en) * | 2017-06-28 | 2019-01-03 | 杭州海康威视数字技术股份有限公司 | White balance adjustment method and apparatus, camera and 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 |
| CN110505459A (en) * | 2019-08-16 | 2019-11-26 | 域鑫科技（惠州）有限公司 | Suitable for the image color correction method of endoscope, device and storage medium |
| CN110794599A (en) * | 2019-10-23 | 2020-02-14 | 联想(北京)有限公司 | Color cast detection method, electronic equipment and computer readable storage medium |
| WO2021051382A1 (en) * | 2019-09-20 | 2021-03-25 | 深圳市大疆创新科技有限公司 | White balance processing method and device, and mobile platform and camera |
| 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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Cited By (22)
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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 |
| CN103974053A (en) * | 2014-05-12 | 2014-08-06 | 华中科技大学 | Automatic white balance correction method based on grey dot extraction |
| CN105828058A (en) * | 2015-05-29 | 2016-08-03 | 维沃移动通信有限公司 | Adjustment method and device of white balance |
| 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 |
| CN104954772A (en) * | 2015-06-26 | 2015-09-30 | 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 |
| CN107404640A (en) * | 2016-05-20 | 2017-11-28 | 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 |
| CN106303473A (en) * | 2016-08-23 | 2017-01-04 | 宁波江丰生物信息技术有限公司 | A kind of white balance adjusting method and camera |
| 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 |
| WO2019001163A1 (en) * | 2017-06-28 | 2019-01-03 | 杭州海康威视数字技术股份有限公司 | White balance adjustment method and apparatus, camera and medium |
| US11323677B2 (en) | 2017-06-28 | 2022-05-03 | Hangzhou Hikvision Digital Technology Co., Ltd. | White balance adjustment method and apparatus, camera and medium |
| CN107920242A (en) * | 2017-12-28 | 2018-04-17 | 努比亚技术有限公司 | A kind of optimization method of automatic white balance, terminal and computer-readable recording 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 |
| CN108093234A (en) * | 2017-12-29 | 2018-05-29 | 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 |
| CN110505459A (en) * | 2019-08-16 | 2019-11-26 | 域鑫科技（惠州）有限公司 | Suitable for the image color correction method of endoscope, device and storage medium |
| WO2021051382A1 (en) * | 2019-09-20 | 2021-03-25 | 深圳市大疆创新科技有限公司 | White balance processing method and device, and mobile platform and camera |
| CN110794599A (en) * | 2019-10-23 | 2020-02-14 | 联想(北京)有限公司 | Color cast detection method, electronic equipment and computer readable storage medium |
| 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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Effective date of registration: 20190611 Address after: 518000 Guangdong 28, Shenzhen, Futian District, Huafu street, No. 5001 Huanggang Road, Shenzhen Industrial upper city (two phase of the Southern District) Patentee after: Shenzhen Sanbao innovation and intelligence Co., Ltd. Address before: 518000 Building No. 209, Times Science and Technology Building, Northeast Side of Junction of Shennan Road and Nongyuan Road, Futian District, Shenzhen City, Guangdong Province Patentee before: Qihan Technology Co., Ltd. |
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