CN102244713B - Image processing device and method - Google Patents
Image processing device and method Download PDFInfo
- Publication number
- CN102244713B CN102244713B CN201010171584.0A CN201010171584A CN102244713B CN 102244713 B CN102244713 B CN 102244713B CN 201010171584 A CN201010171584 A CN 201010171584A CN 102244713 B CN102244713 B CN 102244713B
- Authority
- CN
- China
- Prior art keywords
- pixel
- brightness
- image
- value
- brightness value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Landscapes
- Image Processing (AREA)
Abstract
The invention discloses an image processing device which comprises an image acquisition module, a storage module, a calculation module, a selection module and a brightness adjustment module. The image acquisition module is used for acquiring an image. The storage module is used for storing a quadratic parabolic equation K1=(K0-S)(ar2+br+1)+S, in which K1 is a first brightness value of each pixel point, K0 is an initial brightness value of each pixel point, a is 5*10<-14>, b is 7*10<-6>, r is a square value of number of pixel points between each pixel point and a central pixel point, and S is a light black value of an image sensor of the acquired image. The calculation module is used for calculating the initial brightness value of each pixel point and the square value of number of pixel points between each pixel point and the central pixel point and putting the values to the quadratic parabolic equation to obtain the first brightness value of each pixel point. The selection module is used for selecting whether to adjust the brightness of each pixel point based on the first brightness value. If so, the brightness adjustment module is used for adjusting the brightness of each pixel point based on the first brightness, so that the brightness on the edge of the image is close to the brightness in the central area. The invention also relates to an image processing method.
Description
Technical field
The present invention relates to a kind of image processing apparatus and method.
Background technology
Now the captured image going out of camera module is generally by system level chip (system on a chip, SoC) carry out the subsequent treatment such as brightness adjustment, but because the price comparison of SoC is expensive, in order to reduce production costs, some manufacturer does not generally arrange SoC for image quality in less demanding camera module (such as the camera of some low-end mobile phone) at those, but by the central processing unit of embedded in mobile phone, image is carried out to simple process, but according to prior art, the disposal ability of the central processing unit of embedded in mobile phone is limited, make captured image still have dark angle, be that mid portion is brighter, four corners are darker, therefore how the captured image of the image sensor that does not possess SoC being carried out to brightness adjustment just becomes problem demanding prompt solution.
Summary of the invention
In view of this, be necessary to provide a kind of image processing apparatus and method of effective raising image quality.
An image processing apparatus, it comprises an image collection module, a memory module, a computing module, selects module and a brightness adjustment module for one.Described image collection module is used for obtaining an image, and it comprises an image sensor.In described memory module, store a second-degree parabola equation K
1=(K
0-S) (ar
2+ br+1)+S, wherein K
1for the first brightness value of each pixel, K
0for the original intensity value of each pixel, a is 5 * 10
-14, b is 7 * 10
-6, r be each pixel in described image to the pixel number between central pixel point square, the black value of light that S is described image sensor.Described computing module for calculate the original intensity value of described each pixel of image and each pixel in described image to the pixel number between central pixel point square, then bring in described second-degree parabola equation and calculate, obtain the first brightness value of each pixel.Described selection module is for selecting whether to adjust with the first brightness value the brightness of each pixel according to user's demand.When described selection module is selected to adjust the brightness of each pixel with the first brightness value, described brightness adjustment module is adjusted the brightness of each pixel according to the first brightness value.
An image processing method, it comprises the steps: to take an image; Calculate the original intensity value of each pixel in described image; Calculate each pixel in described image to the square value of the pixel number between central pixel point, and to the square value of the pixel number between central pixel point and the original intensity value of each pixel, bring each pixel in described image into a second-degree parabola equation K
1=(K
0-S) (ar
2+ br+1) in+S, calculate, obtain the first brightness value of each pixel, wherein K
1for the first brightness value of each pixel, K
0for the original intensity value of each pixel, a is 5 * 10
-14, b is 7 * 10
-6, r be each pixel in described image to the square value of the pixel number between central pixel point, S is the black value of light of obtaining the image sensor of image; According to the first brightness value, adjust the brightness of each pixel.
Image processing apparatus of the present invention and method, each pixel is brought in a second-degree parabola equation and calculated to the square value of the pixel number between central pixel point and the original intensity value of each pixel, and according to the first luma component values, the brightness of each pixel is adjusted, thereby the brightness value of pixel that makes the edge of described image more approaches the brightness value of the pixel of central area, make the brightness of described image even, greatly improve image quality.
Accompanying drawing explanation
Fig. 1 is the functional block diagram of the image processing apparatus of better embodiment of the present invention;
Fig. 2 is the schematic diagram of the image of each Color Channel before and after processing through the image processing apparatus described in Fig. 1;
Schematic diagram when Fig. 3 is the coefficient matrix of the 3rd brightness value that calculates described image of the image processing apparatus described in Fig. 1;
Fig. 4 is the flow chart of the image processing method of better embodiment of the present invention.
Main element symbol description
Image processing apparatus 100
Image collection module 10
Separation of images module 20
Memory module 30
Computing module 40
The first computing unit 41
The second computing unit 42
The 3rd computing unit 43
The 4th computing unit 44
The 5th computing unit 45
The 6th computing unit 46
Select module 50
Brightness adjustment module 60
Image synthesis unit 70
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in further detail.
Refer to Fig. 1, a kind of image processing apparatus 100 providing for embodiment of the present invention, it comprises an image collection module 10, a separation of images module 20, a memory module 30,40, one of a computing module is selected 50, one brightness adjustment modules 60 of module and an image synthesis unit 70.
Described image collection module 10 is for taking an image.In the present embodiment, described image collection module 10 is a camera module, and described camera module comprises an image sensor.As an example, in the present embodiment, the number of the pixel of described image sensor is 648*488, and described image sensor output signal is ten bit binary data (10-bit).
Described separation of images module 20 is for being separated into multiple images by described image according to Color Channel.In the present embodiment, as shown in Figure 2, described separation of images module 20 by described image according to four Color Channels (Gr, Gb, R, B) be separated into four images, wherein Gr represents green red channel, Gb represents turquoise passage, and R represents red channel, and B represents blue channel.Described four kinds of color component value are used Gr equally, Gb, and R and B represent, can obtain S=a
1gr+a
2gb+a
3r+a
4b, wherein a
1, a
2, a
3, a
4be coefficient.
In described memory module 30, store a second-degree parabola equation K
1=(K
0-S) (ar
2+ br+1)+S, wherein K
1for the first luma component values of each pixel in every image, K
0for the original intensity component value of each pixel in every image, a is 5 * 10
-14, b is 7 * 10
-6r is that each pixel in every image is to the square value of the pixel number between central pixel point, S is the black value of the light of described image sensor, it is illustrated in described image sensor and does not accept in the situation of illumination, the color component value of this pixel output, such as the data of output signal are the image sensor of eight-digit binary number data (8-bit), its actual light reaction scope is 0～2
8-1 (255), but this image sensor is not in the situation that accepting illumination, still can export non-vanishing light reaction value, therefore needs first by the original intensity component value K of each pixel
0deduct the black value of corresponding light, the brightness component value of each pixel value is changed between normal scope 0～255.Every kind of image sensor all has the black value of corresponding light, such as, the data of output signal are that the black value of light of the image sensor of eight-digit binary number data (8-bit) is 16; Output signal is that the black value of light of the image sensor of ten bit binary data (10-bit) is 64.
Described computing module 40 comprises the first computing unit 41, the second computing unit 42, the three computing unit 43, the four computing unit 44, the five computing units 45 and the 6th computing units 46.
Described the first computing unit 41 is for calculating respectively the original intensity component value K of each pixel of every image
0.
Described the second computing unit 42 is for calculating each pixel of every image to the square value of the number of pixels between central pixel point, then each pixel in described every image is brought in described second-degree parabola equation and calculated to the square value of the number of pixels between central pixel point and the original intensity component value of each pixel, obtain the first luma component values of each pixel.
Described the 3rd computing unit 43 is for centered by a pixel, define a square area, the first luma component values of all pixels in this region is averaged, the second luma component values using this mean value as this pixel, and each pixel in every image is carried out to above-mentioned processing.In the present embodiment, described square area is 45*45 region.Be appreciated that, for the pixel that approaches four top corner regions of every image, if a part of region in the square area of the 45*45 being defined centered by it does not have pixel, so only in described square area the value of the first luma component values of existing pixel after averaging as the first luma component values of corresponding pixel.Be appreciated that owing to being positioned at the brightness of the pixel of central area and be more or less the same, and because described image sensor is rectangle, therefore for central pixel point, calculate the rectangular area that also can only define a 4*8, to reduce amount of calculation.
Described the 4th computing unit 44 is for for every image, respectively the second luma component values of the second luma component values of each pixel and corresponding central pixel point is divided by, and obtains the coefficient matrix of the second luma component values of every image.
Described the 5th computing unit 45 respectively by each pixel along described pixel a plurality of pixels of the outside continuous drawing of direction with the line of corresponding central pixel point, calculate respectively the difference of coefficient of the second luma component values of adjacent two pixels, and obtain the mean value of the plurality of difference, the coefficient of the second luma component values of each pixel is deducted to the mean value of corresponding difference, as the coefficient of the 3rd luma component values of this pixel, thereby obtain the coefficient matrix of the 3rd luma component values of every image.In the present embodiment, the number of the pixel of continuous drawing is 8.Such as, as shown in Figure 3, if the coefficient of the second luma component values of one of them pixel A is 0.99, and this pixel A (is labeled as pixel B along 8 pixels of the outside continuous drawing of direction of the line of itself and central pixel point O, C, D, E, F, G, H, I), the coefficient of the second luma component values of these 8 pixels is respectively 0.96, 0.88, 0.76, 0.64, 0.53, 0.48, 0.31, 0.29, obtain the difference 0.03 of coefficient of the second luma component values of adjacent two pixels, 0.08, 0.12, 0.12, 0.11, 0.05, 0.15, 0.02, the mean value of the difference of these 8 the second luma component values is 0.085, the coefficient of the 3rd luma component values of this pixel A is 0.99-0.085=0.905.
Described the 6th computing unit 46, for respectively the original intensity component value of the coefficient matrix of the 3rd luma component values of every image and corresponding each pixel of original image being multiplied each other, obtains the 3rd luma component values of each pixel in every image.
Described selection module 50 is for selecting with which luma component values to adjust the brightness of each pixel according to user's demand.
Described brightness adjustment module 60 is for adjusting the brightness value of each pixel with the first luma component values, the second luma component values or the 3rd luma component values according to the selection result of described selection module.
Described image synthesis unit 70 is for carrying out brightness adjustment luma component values afterwards according to the synthetic image of corresponding ratio by described multiple images through described brightness adjustment module 60.Be appreciated that according to S=a
1gr+a
2gb+a
3r+a
4b synthesizes described luminance component, wherein a
1, a
2, a
3, a
4be coefficient.
Referring to Fig. 4, is a kind of image processing method that embodiment of the present invention provides, and it comprises the steps:
S1: take an image.
S2: described image is carried out to separation according to Color Channel.In the present embodiment, described image is according to four Color Channels (Gr, Gb, R, B) carry out separation, be isolated into four images (as shown in Figure 2), wherein Gr represents green red channel, Gb represents turquoise passage, and R represents red channel, and B represents blue channel.Be appreciated that also and can image do not carried out to separation, after step S2, directly proceed to step S4.But described image is carried out after separation according to four Color Channels (Gr, Gb, R, B), then carry out brightness adjustment, can reduce the image of different color channels to the interference of brightness each other, make the better effects if of brightness adjustment.
S3: the original intensity component value K that calculates respectively each pixel in every image
0.
S4: calculate each pixel in every image to the square value of the pixel number between central pixel point, and bring respectively each pixel in described every image into second-degree parabola equation K to the square value of the pixel number between central pixel point and the original intensity component value of described each pixel
1=(K
0-S) (ar
2+ br+1) in+S, calculate, wherein K
1for the first luma component values of each pixel in every image, K
0for the original intensity component value of each pixel in every image, a is 5 * 10
-14, b is 7 * 10
-6, r be each pixel in every image to the square value of pixel number between central pixel point, S is the black value of light of obtaining the image sensor of image.
S5: whether selection is according to the brightness of every image of the first luma component values adjustment.
S6: if so, adjust the brightness of every image according to the first luma component values, proceed to step S14.
S7: if not, centered by a pixel, define a foursquare region, the first luma component values of all pixels in this region is averaged, the second luma component values using this mean value as this pixel, and each pixel in every image is carried out to above-mentioned processing, the brightness of every image is carried out to further homogenizing processing.
S8: whether selection is according to the brightness of every image of the second luma component values adjustment.
S9: if so, adjust the brightness of every image according to the second luma component values, proceed to step S14.
S10: if not, for every image, respectively the second luma component values of the second luma component values of each pixel and described central pixel point is divided by, obtains the coefficient matrix of the second luma component values of every image.
S11: for every image, a plurality of pixels of the outside continuous drawing of direction along the line of described pixel and central pixel point by each pixel respectively, calculate respectively the difference of the coefficient of adjacent two pixels, and obtain the mean value of the plurality of difference, the coefficient of the second luma component values of each pixel is deducted to the mean value of corresponding difference, as the coefficient of the 3rd luma component values of each pixel, thereby obtain the coefficient matrix of the 3rd luma component values of every image.
S12: respectively the original intensity component value of each pixel in the coefficient matrix of the 3rd luma component values of every image and corresponding original image is multiplied each other, obtain the 3rd luma component values of every image.
S13: adjust the brightness of each pixel in every image according to the 3rd luma component values.
As shown in Table 1, be the deck watch of the luma component values of every image before and after brightness adjustment.As can be seen from the table, after (1) brightness adjustment, average the 3rd luma component values of every image all promotes to some extent; (2) before brightness adjustment, the standard deviation of the original intensity component value of every image is more than 17, and after brightness adjustment, the standard deviation of the 3rd luma component values of every image all narrows down in 8, proves thus, and the brightness ratio after every image is processed is more even.
Table one
| Gr Channel | Gb Channel | R Channel | B Channel | |
| The average original intensity component value of original image | 162.45 | 163.06 | 116.51 | 120.73 |
| The standard deviation of the original intensity component value of original image | 24.76 | 24.79 | 19.60 | 17.16 |
| Average the 3rd luma component values after image is processed | 219.20 | 220.02 | 156.91 | 163.37 |
| The standard deviation of the 3rd luma component values after image is processed | 6.57 | 7.08 | 3.23 | 6.91 |
S14: the luma component values after the process brightness adjustment of each pixel in four images is synthesized to an image according to corresponding ratio.If be appreciated that, described image processing method does not comprise step S2, described image is not carried out to separated step according to Color Channel, does not just need this step S14 yet.
Image processing apparatus of the present invention and method, each pixel is brought in a second-degree parabola equation and calculated to the distance of central pixel point and the original intensity component value of each pixel, obtain the first luma component values of each pixel, thereby the brightness of described image is carried out to preliminary homogenizing processing.In order to make the brightness of described image more even, described image processing apparatus also the value after the first luma component values of each pixel a plurality of pixels around averages as the second luma component values of corresponding pixel points, then the second luma component values of the second luma component values of each pixel and central pixel point is divided by, obtain the coefficient matrix of the second luma component values, by the computing of successively decreasing of the coefficient matrix of this two luma component values, obtain the coefficient matrix of the 3rd luma component values of every image, again the original intensity component value of each pixel in the image of the coefficient matrix of the 3rd luma component values and corresponding Color Channel is multiplied each other, the luma component values after each pixel that obtains every image is adjusted, according to the 3rd luma component values, the brightness value of each pixel is adjusted, finally four images after brightness adjustment are synthesized, thereby the brightness value that makes the edge of every image after brightness adjustment more approaches the luma component values of central area, make the brightness of described image even, greatly improve image quality.
Be understandable that, for the person of ordinary skill of the art, can make other various corresponding changes and distortion by technical conceive according to the present invention, and all these change and distortion all should belong to the protection range of the claims in the present invention.
Claims (9)
1. an image processing apparatus, it comprises an image collection module, a memory module, a computing module, selects module and a brightness adjustment module for one, and described image collection module is used for obtaining an image, and it comprises an image sensor; In described memory module, store a second-degree parabola equation K
1=(K
0-S) (ar
2+ br+1)+S, wherein K
1for the first brightness value of each pixel, K
0for the original intensity value of each pixel, a is 5 * 10
-14, b is 7 * 10
-6, r be each pixel in described image to the pixel number between central pixel point square, the black value of light that S is described image sensor; Described computing module for calculate the original intensity value of described each pixel of image and each pixel in described image to the pixel number between central pixel point square, then bring in described second-degree parabola equation and calculate, obtain the first brightness value of each pixel; Described selection module is for selecting whether to adjust with the first brightness value the brightness of each pixel according to user's demand; When described selection module is selected to adjust the brightness of each pixel with described the first brightness value, described brightness adjustment module is adjusted the brightness of each pixel according to described the first brightness value.
2. image processing apparatus as claimed in claim 1, is characterized in that, the number of the pixel of the image sensor in described image collection module is 648*488, and described image sensor institute output signal is ten bit binary data, and the black value S of described light is 64.
3. image processing apparatus as claimed in claim 1, it is characterized in that, when described selection module is selected not adjust the brightness of each pixel according to the first brightness value, described computing module is also for calculating the second brightness value of each pixel, its computational methods are: centered by calculated pixel, define a foursquare region, the first brightness value of all pixels in this region is averaged, the second brightness value using this mean value as this calculated pixel; Described selection module is also for selecting whether to adjust according to described the second brightness value the brightness of each pixel according to user's demand, when described in described selection module selective basis, the second brightness value is adjusted the brightness of each pixel, described brightness adjustment module is adjusted the brightness of each pixel according to described the second brightness value.
4. image processing apparatus as claimed in claim 3, it is characterized in that, when described selection module is selected not adjust the brightness of each pixel according to the second brightness value, described computing module also, for respectively the second brightness value of the second brightness value of each pixel and corresponding central pixel point being divided by, obtains the coefficient matrix of the second brightness value of every image; Respectively by each pixel along itself a plurality of points of the outside continuous drawing of direction with the line of corresponding central pixel point, calculate respectively the difference of the coefficient of adjacent 2, and obtain the mean value of the plurality of difference, the coefficient of each pixel is deducted to the mean value of corresponding difference, as the coefficient of the 3rd brightness value of this pixel, thereby obtain the coefficient matrix of the 3rd brightness value of each pixel of described image; Then respectively the original intensity value of the coefficient matrix of the 3rd brightness value of described image and each pixel is multiplied each other, obtain the 3rd brightness value, described brightness adjustment module is adjusted the brightness of each pixel according to described the 3rd brightness value.
5. image processing apparatus as claimed in claim 1, it is characterized in that, described image processing apparatus also comprises a separation of images module and image synthesis unit, described separation of images module is for becoming to be separated into multiple images by described image according to Color Channel, described computing module, selection module and brightness adjustment module are adjusted the brightness of each pixel in described multiple images respectively, and described image synthesis unit is for synthesizing an image by multiple images through after brightness adjustment.
6. an image processing method, it comprises the steps: to take an image; Calculate the original intensity value of each pixel in described image; Calculate each pixel in described image to the square value of the number of pixels between central pixel point, and to the square value of the number of pixels between central pixel point and the original intensity value of each pixel, bring respectively each pixel in described image into a second-degree parabola equation K
1=(K
0-S) (ar
2+ br+1) in+S, calculate, obtain the first brightness value K of each pixel
1, K wherein
1for the first brightness value of each pixel, K
0for the original intensity value of each pixel, a is 5 * 10
-14, b is 7 * 10
-6, r be each pixel to the square value of the pixel number between central pixel point, S is the black value of light of obtaining the image sensor of image; Select whether according to described the first brightness value, to adjust the brightness of each pixel, if so, according to described the first brightness value, adjust the brightness of each pixel.
7. image processing method as claimed in claim 6, it is characterized in that, if select not adjust according to described the first brightness value the brightness of each pixel, calculate the second brightness value of each pixel, computational methods are: in described image, centered by calculated pixel, define a region, the first brightness value of all pixels in this region is averaged to the second brightness value using this mean value as calculated pixel; Select whether according to described the second brightness value, to adjust the brightness of each pixel, if so, according to described the second brightness value, adjust the brightness of each pixel.
8. image processing method as claimed in claim 7, it is characterized in that, if select not adjust according to described the second brightness value the brightness of each pixel, the second brightness value of the second brightness value of each pixel in described image and described central pixel point is divided by, obtains the coefficient matrix of the second brightness value; A plurality of points of the outside continuous drawing of direction by each pixel in the coefficient matrix of described the second brightness value along the line of itself and central pixel point, calculate the difference of the coefficient between adjacent two pixels, and obtain the mean value of the plurality of difference, the coefficient of each pixel is deducted to the mean value of corresponding difference, as the coefficient of the 3rd brightness value of each pixel, thereby obtain the coefficient matrix of the 3rd brightness value of described image; The original intensity value of the coefficient matrix of the 3rd brightness value of described image and each pixel is multiplied each other, obtain the 3rd brightness value of each pixel in described image; According to described the 3rd brightness value, adjust the brightness of each pixel.
9. image processing method as claimed in claim 8, it is characterized in that, after taking an image, also comprise and described image is separated into the step of multiple images according to Color Channel, and described multiple images all carry out respectively step as claimed in claim 8 successively, and after adjusting the brightness of each pixel according to described the 3rd brightness value, also comprise the step of the synthetic image of described multiple images.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010171584.0A CN102244713B (en) | 2010-05-13 | 2010-05-13 | Image processing device and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010171584.0A CN102244713B (en) | 2010-05-13 | 2010-05-13 | Image processing device and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102244713A CN102244713A (en) | 2011-11-16 |
| CN102244713B true CN102244713B (en) | 2014-10-15 |
Family
ID=44962529
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201010171584.0A Expired - Fee Related CN102244713B (en) | 2010-05-13 | 2010-05-13 | Image processing device and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102244713B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102905077B (en) * | 2012-10-09 | 2014-12-17 | 深圳市掌网立体时代视讯技术有限公司 | Image vignetting brightness regulating method and device |
| CN110706161B (en) * | 2019-08-22 | 2022-07-19 | 稿定（厦门）科技有限公司 | Image brightness adjusting method, medium, device and apparatus |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6246445B1 (en) * | 1998-08-04 | 2001-06-12 | Samsung Electronics Co., Ltd. | Brightness correcting circuit and method for efficiently correcting brightness at edge and corner of monitor screen |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2924615B2 (en) * | 1993-11-10 | 1999-07-26 | 日本ビクター株式会社 | Display device |
-
2010
- 2010-05-13 CN CN201010171584.0A patent/CN102244713B/en not_active Expired - Fee Related
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6246445B1 (en) * | 1998-08-04 | 2001-06-12 | Samsung Electronics Co., Ltd. | Brightness correcting circuit and method for efficiently correcting brightness at edge and corner of monitor screen |
Non-Patent Citations (1)
| Title |
|---|
| JP平7－135616A 1995.05.23 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102244713A (en) | 2011-11-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11849224B2 (en) | Global tone mapping | |
| US8310567B2 (en) | Methods of modeling an integrated noise in an image sensor and methods of reducing noise using the same | |
| CN101193314B (en) | Image processing device and method for image sensor | |
| US8023014B2 (en) | Method and apparatus for compensating image sensor lens shading | |
| CN102835102B (en) | Image processing apparatus and control method for image processing apparatus | |
| US8059169B2 (en) | Apparatus and method for compensating color, and image processor, digital processing apparatus, recording medium using it | |
| US8781225B2 (en) | Automatic tone mapping method and image processing device | |
| CN107038680A (en) | The U.S. face method and system that adaptive optical shines | |
| CN113168669B (en) | Image processing method, device, electronic equipment and readable storage medium | |
| US20080292184A1 (en) | Apparatus and method for automatically adjusting white balance | |
| CN112669758A (en) | Display screen correction method, device, system and computer readable storage medium | |
| US20200228770A1 (en) | Lens rolloff assisted auto white balance | |
| US8559747B2 (en) | Image processing apparatus, image processing method, and camera module | |
| CN107644437B (en) | Color cast detection system and method based on blocks | |
| WO2019104047A1 (en) | Global tone mapping | |
| US9270872B2 (en) | Apparatus, systems, and methods for removing shading effect from image | |
| US7609300B2 (en) | Method and system of eliminating color noises caused by an interpolation | |
| CN110807735A (en) | Image processing method, image processing device, terminal equipment and computer readable storage medium | |
| CN114998122A (en) | Low-illumination image enhancement method | |
| CN102244713B (en) | Image processing device and method | |
| US9113121B2 (en) | Method for white balance adjustment of images | |
| US20200228769A1 (en) | Lens rolloff assisted auto white balance | |
| CN102243760B (en) | Image black spot search system and method | |
| WO2022032666A1 (en) | Image processing method and related apparatus | |
| KR101143834B1 (en) | Aparatus and metod for controlling auto white balance |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20141015 Termination date: 20160513 |