CN101286231B - Contrast enhancement method for uniformly distributing image brightness - Google Patents
Contrast enhancement method for uniformly distributing image brightness Download PDFInfo
- Publication number
- CN101286231B CN101286231B CN2008100446303A CN200810044630A CN101286231B CN 101286231 B CN101286231 B CN 101286231B CN 2008100446303 A CN2008100446303 A CN 2008100446303A CN 200810044630 A CN200810044630 A CN 200810044630A CN 101286231 B CN101286231 B CN 101286231B
- Authority
- CN
- China
- Prior art keywords
- range
- sub
- gray level
- input picture
- gray
- 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
Images
Landscapes
- Facsimile Image Signal Circuits (AREA)
- Image Processing (AREA)
Abstract
The invention relates to a contrast enhancing method of brightness of an evenly distributed image, which comprises the specific steps: a. the image is input, the display range from 0 to 255 of the whole gray is evenly divided into at least two continuous sub-regions as the target sub-regions for the mapping of the input image; b. the distribution of a histogram of the input image is calculated, thus counting the number of pixels which are corresponding to each gray level; c. the gray levels of the input image are divided into continuous sub-regions with the same number of the target sub-regions, and the number of the pixels corresponded by the gray level of each sub-region is roughly equal; d. and each continuous gray level sub-region of the input image is mapped to the target sub-regions divided from the gray range from 0 to 255. Compared with the histogram equalization processing method, the method can not only increase the visual distance between the pixels, but also better maintain the details of the image.
Description
Technical field
The invention belongs to Digital Image Processing and video display technology field, be specifically related to a kind of picture contrast Enhancement Method of uniformly distributing image brightness.
Background technology
It is one of important technology in the digital image processing field that picture contrast strengthens, and by regulating the distribution of image gray levels, can increase the visible sensation distance between each pixel, makes fuzzy target easy identification, improves the viewing quality of image.Histogram equalization is modal picture contrast enhancement process method, this method is sought the gray level of the output image after the conversion according to the cumulative probability density of each gray level of input picture, according to the cumulative distribution function that calculates, set up the corresponding relation between input picture and the output image gray scale.It can play good effect to strengthening general pattern, but when the shared grey level number of image is considerably less, histogram equalization can be expanded several gray levels that contain a large amount of pixels to such an extent that hold very much, and have only the gray level of small number of pixels point seriously to be pushed, occur excessively strengthening, it is bright or dark excessively that enhancing back image is crossed, and is the histogram of an input picture as Fig. 3, and Fig. 4 is the histogram among Fig. 3 is handled the back output image through histogram equalization a histogram; By the contrast of two width of cloth drawings, can clearly reflect the limitation of prior art.
Summary of the invention
The technical problem to be solved in the present invention is the deficiency at existing picture contrast enhancement process method, proposes a kind of picture contrast Enhancement Method of uniformly distributing image brightness.
The present invention solves the problems of the technologies described above the technical scheme that is adopted, not the gray level of seeking the output image after the conversion according to the cumulative probability density of each gray level of input picture, but with the continuous gray-scales interval mapping that contains same pixel point of an input picture gray level interval with fixed grey level number to output image.Not only make the intensity profile of output image even like this after the conversion, and because the number of greyscale levels in the gray level interval of output image fix rather than determine by the cumulative probability density of gray level, so some gray level that can overcome input picture is by hyper expanded and the phenomenon that other gray levels are seriously pushed.
The present invention is that the concrete grammar that solves the problems of the technologies described above the technical scheme that is adopted is: a kind of contrast enhancement process of uniformly distributing image brightness comprises following concrete steps:
A. input picture, and whole gray scale indication range 0~255 is equally divided into 16 continuous sub-ranges, be respectively L
1[0,15], L
2[16,31] ... L
16[240,255] are as the target sub-range of input picture mapping;
B. the histogram distribution of calculating input image is added up the pixel number of each gray level correspondence;
C. the gray level with input picture is divided into the continuous sub-range identical with target sub-range quantity,
The specific implementation method of this step may further comprise the steps:
C1. the minimum gray level Min of calculating input image and high grade grey level Max;
If c2. the input picture size is M * N, the grey level range Min~Max of whole input picture is divided into 16 continuous gray level sub-range L
1' [Min, x
1], L
2' [x
1+ 1, x
2] ... L
16' [x
15+ 1, Max];
And the pixel number of gray level correspondence all is in Mean ± Setover scope, wherein in each sub-range
M * N is that the size of input picture is the picture element sum;
D. each the continuous gray level sub-range with input picture is mapped to by on the target sub-range that marks off between 0~255 gray area, and its specific implementation method may further comprise the steps:
D1. at first add up sub-range L
i' [x
I-1+ 1, x
i] in number of greyscale levels n;
D2. as if n<8, with sub-range L
i' [x
I-1+ 1, x
i] in n gray level be mapped to sub-range L
iIn [16 * (i-1), 16 * i-1], and the gray level after the feasible mapping is with sub-range L
i[16 * (i-1), 16 * i-1] are divided into the n+1 equal portions, in this step with sub-range L
i' [x
I-1+ 1, x
i] the concrete formula that is mapped on the target sub-range is:
L ' is the gray level of interval i in the input picture in this formula, and L is the gray level of L ' mapping back target interval;
D3. if n 〉=8, then these grey scale linear ground are stretched or be compressed to sub-range L
iOn [16 * (i-1), 16 * i-1] last 16 gray levels, in this step with sub-range L
i' [x
I-1+ 1, x
i] the concrete formula that is mapped on the target sub-range is:
L ' is the gray level of interval i in the input picture in this formula, and L is the gray level of L ' mapping back target interval.
Beneficial effect concrete manifestation of the present invention is in the following areas: the method expansion or the compression gray level that adopt histogram equalization, a lot of gray levels all are not used, and the present invention utilizes the gray level segmentation, with the continuous gray-scales interval mapping of the different length of input picture to the identical continuous target sub-range of 16 length of gray scale indication range between 0~255, if number of greyscale levels is few in the input picture gray level sub-range, these gray levels are inserted in the target sub-range in inciting somebody to action so, increased the brightness distance between each gray level in so not only interval, and also increased with the distance in adjacent other interval, made full use of each gray level.Compare with the histogram equalization disposal route, the present invention can not only increase the visible sensation distance between the pixel, also can better keep image detail simultaneously.
Description of drawings
Fig. 1 is the process flow diagram of contrast enhancement process of the present invention.
Fig. 2 is the process flow diagram that each continuous sub-range of input picture of the present invention is mapped to the target sub-range.
Fig. 3 is the histogram of the input picture of one embodiment of the invention.
Fig. 4 is the histogram of Fig. 3 is handled the back output image through histogram equalization a histogram.
Fig. 5 is the histogram of Fig. 3 is handled the back output image through a method of the present invention histogram.
Embodiment
The invention will be further described below in conjunction with the drawings and specific embodiments.
Fig. 3 is the histogram of an input picture, in conjunction with the process flow diagram of Fig. 1 and Fig. 2 this input picture is handled.
(1) input picture, and whole gray scale indication range 0~255 is equally divided into 16 sub-ranges, be respectively L
1[0,15], L
2[16,31] ... L
16[240,255] are as the target sub-range of input picture mapping.
(2) ask the input picture histogram distribution, add up the pixel number of each gray level correspondence.
(3) minimum gray level of calculating input image and high grade grey level Min, Max.
(4) add up to M * N if the input picture size is a picture element, the grey level range Min~Max with whole input picture is divided into 16 continuous gray level sub-range L equally
1' [Min, x
1], L
2' [x
1+ 1, x
2] ... L
16' [x
15+ 1, Max].
(4a) gray level with input picture is distributed into 16 gray level sub-ranges that length is identical, and
The pixel number of supposing each gray level sub-range correspondence is identical, and the interval corresponding pixel number of each gray level is so:
(4b) still the pixel number of different gray level correspondences has nothing in common with each other, so a deviate is set
After making that like this input picture gray level is divided, the interval corresponding pixel number of each gray level all is in Mean ± Setover scope.
(5) the gray level sub-range L that input picture is divided
i' [x
I-1+ 1, x
i] in gray level be mapped to target sub-range L
iOn the gray level in [16 * (i-1), 16 * i-1].
As described in step (5), the specific practice that the continuous gray-scales sub-range of an input picture is transformed to the target sub-range is:
(5a) at first add up input picture sub-range L
i' [x
I-1+ 1, x
i] in number of greyscale levels n;
(5b) as if n<8, with sub-range L
i' [x
I-1+ 1, x
i] in n continuous gray-scales be mapped to sub-range L
iIn [16 * (i-1), 16 * i-1], and the gray level after the feasible mapping is with sub-range L
i[16 * (i-1), 16 * i-1] are divided into the n+1 equal portions.
In the above-mentioned steps each continuous gray level sub-range of input picture is mapped to the concrete formula on the target sub-range:
In this formula, L ' is the gray level of interval i in the input picture, L is the gray level of L ' mapping back target interval. formula has been realized and will be inserted in a few gray level in the sub-range of input picture on 16 gray levels of target interval, in the sub-range such as input picture 3 gray levels are arranged, so through being distributed in after the mapping on the 4th, the 8th on 16 grades of gray level intervals of target interval and the 12 gray level.
(5c) if n 〉=8, then these grey scale linear ground are stretched or be compressed to sub-range L
iOn [16 * (i-1), 16 * i-1] last 16 gray levels.
In the above-mentioned steps each continuous gray level sub-range of input picture is mapped to the concrete formula on the target sub-range:
The implication of symbol is identical in the symbol step (5b) in this formula.
Each gray level sub-range L of input picture
i' [x
I-1+ 1, x
i] all be mapped to new target sub-range after, finished the picture contrast enhancing, as Fig. 5 is the histogram of the histogram of Fig. 3 through method processing of the present invention back output image, compare with the histogram of output image after the histogram equalization method of prior art among Fig. 4 is handled, the present invention can not only increase the visible sensation distance between the pixel, also can better keep image detail simultaneously.
Those of ordinary skill in the art will appreciate that embodiment described here is in order to help reader understanding's principle of the present invention, should to be understood that the protection domain of inventing is not limited to such special statement and embodiment.Everyly make various possible being equal to according to foregoing description and replace or change, all be considered to belong to the protection domain of claim of the present invention.
Claims (1)
1. the contrast enhancement process of a uniformly distributing image brightness is characterized in that, comprises following concrete steps:
A. input picture, and whole gray scale indication range 0~255 is equally divided into 16 continuous sub-ranges, be respectively L
1[0,15], L
2[16,31] ... L
16[240,255] are as the target sub-range of input picture mapping;
B. the histogram distribution of calculating input image is added up the pixel number of each gray level correspondence;
C. the gray level with input picture is divided into the continuous sub-range identical with target sub-range quantity, and the specific implementation method of this step may further comprise the steps:
C1. the minimum gray level Min of calculating input image and high grade grey level Max;
If c2. the input picture size is M * N, the grey level range Min~Max of whole input picture is divided into 16 continuous gray level sub-range L
1' [Min, x
1], L
2' [x
1+ 1, x
2] ... L
16' [x
15+ 1, Max];
And the pixel number of gray level correspondence all is in Mean ± Setover scope, wherein in each sub-range
M * N is that the size of input picture is the picture element sum;
D. each the continuous gray level sub-range with input picture is mapped to by on the target sub-range that marks off between 0~255 gray area, and its specific implementation method may further comprise the steps:
D1. at first add up sub-range L
i' [x
I-1+ 1, x
i] in number of greyscale levels n;
D2. as if n<8, with sub-range L
i' [x
I-1+ 1, x
i] in n gray level be mapped to sub-range L
iIn [16 * (i-1), 16 * i-1], and the gray level after the feasible mapping is with sub-range L
i[16 * (i-1), 16 * i-1] are divided into the n+1 equal portions, in this step with sub-range L
i' [x
I-1+ 1, x
i] the concrete formula that is mapped on the target sub-range is:
In this formula L ' be in the input picture interval i-individual gray level, L is the gray level of L ' mapping back target interval;
D3. if n 〉=8, then these grey scale linear ground are stretched or be compressed to sub-range L
iOn [16 * (i-1), 16 * i-1] last 16 gray levels, in this step with sub-range L
i' [x
I-1+ 1, x
i] the concrete formula that is mapped on the target sub-range is:
L ' is the gray level of interval i in the input picture in this formula, and L is the gray level of L ' mapping back target interval.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN2008100446303A CN101286231B (en) | 2008-06-04 | 2008-06-04 | Contrast enhancement method for uniformly distributing image brightness |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN2008100446303A CN101286231B (en) | 2008-06-04 | 2008-06-04 | Contrast enhancement method for uniformly distributing image brightness |
Publications (2)
Publication Number | Publication Date |
---|---|
CN101286231A CN101286231A (en) | 2008-10-15 |
CN101286231B true CN101286231B (en) | 2010-08-11 |
Family
ID=40058422
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN2008100446303A Expired - Fee Related CN101286231B (en) | 2008-06-04 | 2008-06-04 | Contrast enhancement method for uniformly distributing image brightness |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN101286231B (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
TWI823711B (en) * | 2022-12-12 | 2023-11-21 | 大陸商集創北方(深圳)科技有限公司 | Contrast adjustment module, display driver chip, display device and information processing device |
Families Citing this family (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101437114B (en) * | 2008-12-12 | 2010-06-02 | 深圳市斯尔顿科技有限公司 | Method and system for regulating image brightness |
CN102306380B (en) * | 2011-09-14 | 2013-03-27 | 山东省科学院海洋仪器仪表研究所 | Histogram debugging method of colored image and debugging system thereof |
CN103886550B (en) * | 2012-12-24 | 2017-12-01 | 合肥市腾讯信息科技有限公司 | Sketch texture method of adjustment and system |
CN104063845B (en) * | 2013-03-22 | 2018-07-10 | 晨星半导体股份有限公司 | Enhance the method and device and non-transitory computer-readable media of image contrast |
CN104424633B (en) * | 2013-08-23 | 2018-01-12 | 浙江大华技术股份有限公司 | A kind of video contrast's method for detecting abnormality and device |
CN104574326B (en) * | 2013-10-15 | 2017-07-18 | 无锡华润矽科微电子有限公司 | The method and apparatus that histogram equalization processing is carried out to image |
CN104574328A (en) * | 2015-01-06 | 2015-04-29 | 北京环境特性研究所 | Color image enhancement method based on histogram segmentation |
CN104700096B (en) * | 2015-03-30 | 2018-07-13 | 北京奇艺世纪科技有限公司 | A kind of user action identified areas based on image determines method and device |
CN105427256B (en) * | 2015-11-18 | 2018-06-26 | 浙江大华技术股份有限公司 | A kind of infrared image enhancing method and device |
CN105898369A (en) * | 2015-12-01 | 2016-08-24 | 乐视云计算有限公司 | Video image quality adjustment method and device |
CN107292829B (en) * | 2016-03-31 | 2020-12-15 | 阿里巴巴集团控股有限公司 | Image processing method and device |
CN106340278B (en) * | 2016-10-13 | 2019-02-22 | 深圳市华星光电技术有限公司 | A kind of driving method and device of display panel |
CN108073884A (en) * | 2016-11-17 | 2018-05-25 | 浙江工商大学 | A kind of image pre-processing method for lane detection |
CN108877735B (en) | 2017-05-12 | 2021-01-26 | 京东方科技集团股份有限公司 | Gray scale brightness adjusting method and adjusting device of display equipment |
CN108846834B (en) * | 2018-05-31 | 2020-11-20 | 清华大学 | Medical image processing apparatus and medical image processing method |
CN109544483B (en) * | 2018-12-26 | 2021-09-24 | 深圳朗田亩半导体科技有限公司 | Video image brightness and contrast enhancement method and device |
CN112884659A (en) * | 2019-11-29 | 2021-06-01 | 深圳市万普拉斯科技有限公司 | Image contrast enhancement method and device and display equipment |
CN116703888B (en) * | 2023-07-28 | 2023-10-20 | 菏泽城建新型工程材料有限公司 | Auxiliary abnormality detection method and system for bored pile construction |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP0772158A2 (en) * | 1995-10-30 | 1997-05-07 | Hewlett-Packard Company | Image processing system |
WO2007024407A1 (en) * | 2005-08-24 | 2007-03-01 | Intel Corporation | Techniques to improve contrast enhancement using a luminance histogram |
CN1946138A (en) * | 2006-10-19 | 2007-04-11 | 四川长虹电器股份有限公司 | Method for image greyscale histogram equalizing treatment |
WO2007050340A1 (en) * | 2005-10-21 | 2007-05-03 | Carestream Health, Inc. | Method for enhanced visualization of medical images |
-
2008
- 2008-06-04 CN CN2008100446303A patent/CN101286231B/en not_active Expired - Fee Related
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP0772158A2 (en) * | 1995-10-30 | 1997-05-07 | Hewlett-Packard Company | Image processing system |
WO2007024407A1 (en) * | 2005-08-24 | 2007-03-01 | Intel Corporation | Techniques to improve contrast enhancement using a luminance histogram |
WO2007050340A1 (en) * | 2005-10-21 | 2007-05-03 | Carestream Health, Inc. | Method for enhanced visualization of medical images |
CN1946138A (en) * | 2006-10-19 | 2007-04-11 | 四川长虹电器股份有限公司 | Method for image greyscale histogram equalizing treatment |
Non-Patent Citations (1)
Title |
---|
张俊华,杨根,徐青.基于分段线性变换的图像增强.第十四届全国图象图形学学术会议论文集2008年.2008,2008年43-46. * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
TWI823711B (en) * | 2022-12-12 | 2023-11-21 | 大陸商集創北方(深圳)科技有限公司 | Contrast adjustment module, display driver chip, display device and information processing device |
Also Published As
Publication number | Publication date |
---|---|
CN101286231A (en) | 2008-10-15 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN101286231B (en) | Contrast enhancement method for uniformly distributing image brightness | |
CN103353982B (en) | A kind of tone mapping method based on histogram equalization | |
CN104167194B (en) | Liquid crystal display panel gray-scale value setting method and liquid crystal display | |
CN102682436B (en) | A kind of image enchancing method theoretical improved multiple dimensioned Retinex | |
CN103916669A (en) | High dynamic range image compression method and device | |
CN102376082B (en) | Image processing method and device based on gamma correction | |
CN102231791B (en) | Video image defogging method based on image brightness stratification | |
CN106886386A (en) | The method that high-dynamics image is generated from low dynamic image | |
CN110264459A (en) | A kind of interstices of soil characteristics information extraction method | |
CN107767349B (en) | A kind of method of Image Warping enhancing | |
CN103716503B (en) | Image processing apparatus and projector | |
CN104008528B (en) | Nonuniform illumination Underwater Target Detection image enchancing method based on Threshold segmentation | |
CN104574328A (en) | Color image enhancement method based on histogram segmentation | |
CN103534728B (en) | Method and apparatus for setting contrast | |
CN105184759A (en) | Image self-adaptive enhancement method based on histogram compactness transformation | |
CN106339994A (en) | Image enhancement method | |
CN103700077B (en) | A kind of method for adaptive image enhancement based on human-eye visual characteristic | |
CN111951172A (en) | Image optimization method, device, equipment and storage medium | |
CN116137022B (en) | Data enhancement method for underground mining remote monitoring | |
CN105894506A (en) | Face image fuzziness computing method and device | |
CN103680448B (en) | Method for calculating overdrive target value | |
CN106056062B (en) | A kind of vehicle checking method based on adaptive local feature background model | |
CN103208107A (en) | Terminal and method and device for repairing image | |
CN103514588B (en) | Image enchancing method and system | |
CN103839231A (en) | Image enhancement method based on maximization of human vision minimum detection probability |
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 |
Granted publication date: 20100811 Termination date: 20160604 |