CN100563312C - A kind of contrast enhancement process - Google Patents
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Abstract
The invention discloses a kind of contrast enhancement process, comprise the step that overall contrast is adjusted, this step adopts the histogram equalization method, described histogram equalization method limits the greatest gradient of resulting grey scale mapping function, and it is realized by following manner: the pixel that pixel count in histogrammic each tonal gradation of present image is surpassed first threshold value is evenly distributed in described each tonal gradation once more.The invention enables the image after the processing can keep mean flow rate, and strengthened the light and shade contrast, can not cross the noise that strengthens in the image, effectively improved contrast, make display effect more natural.
Description
Technical field
The invention belongs to technical field of image processing, relate in particular to a kind of contrast enhancement process.
Background technology
At video reception end (for example television set, display etc.), because multiple factor affecting such as video acquisition, processing, transmission, reception, often the visual experience effect is undesirable for the video image that people watch, improper as illumination condition, cause that the image full width is dark partially or bright partially, also have contrast deficiency that factors such as luminance dynamic range is not enough or non-linear cause etc.These factors all can have influence on subjective viewing effect, and therefore, enhancing contrast ratio becomes needs a major issue solving in the Video processing.
Usually people can pay attention to the whole structure and the details effect of image simultaneously when watching television image.Accordingly, the contrast enhancement process in existing video frequency processing chip also is divided into two big classes: overall Enhancement Method and local enhancement methods.Wherein, overall Enhancement Method mainly is to reach the purpose that contrast strengthens by revising the image histogram distribution; And local enhancement methods is a pre-defined local contrast, strengthens this local contrast then and reaches the effect that strengthens image detail.
It is the simplest overall Enhancement Method that linear contrast stretches, but linear contrast drawing process can not promote all parts of image simultaneously.When if the image histogram feature has long " hangover ", linear stretch is just inapplicable.The histogram equalization method has the simple and effective advantage of algorithm, on contrast enhancement processing, use more, it is near equally distributed histogram with original histogram transformation, expand to whole tonal range, thereby regulate the dynamic range of image, but traditional histogram equalization can not keep the mean flow rate of image.
At document Duan Jiang, Qiu Guo-ping, Novel histogram processing for colourimage enhancement[A] [M], Third International Conference on Image and Graphics, 2004. in the histogram equalization method is improved, try hard between histogram equalization and the original pixel brightness contribution of image, average out reinforced effects, but noise strengthens obviously, and the light and shade contrast is undesirable.
In the local enhancement methods, document Zeyun Yu, Chandrajit Bajaj.A fast and adaptive methodfor image contrast enhancement[J] .International conference on image processing (ICIP), 2004:1001-1004 has introduced LRM (Local Range Modification, local modification) algorithm, utilized local statistic (as maximum/minimum/mean value etc.) transfer function, this algorithm computation amount is bigger.
Self-adapting histogram equilibrium (AHE) method all adopts the identical sliding window of size to each pixel in the image, carry out partial equilibriumization then in this window, to realize the processing to the window center pixel.Though the image reinforced effects of local auto-adaptive equalization method is obvious, and can keep image detail, algorithm is relatively complicated, promptly will do the subwindow partial equilibriumization to each pixel of image, and amount of calculation is very big.
Summary of the invention
Technical problem to be solved by this invention provides the contrast enhancement process that a kind of contrast is adjusted better effects if.
In order to solve the problems of the technologies described above, the present invention proposes a kind of contrast enhancement process, comprise the step that overall contrast is adjusted, this step adopts the histogram equalization method, described histogram equalization method limits the greatest gradient of resulting grey scale mapping function, and it is realized by following manner: the pixel that pixel count in histogrammic each tonal gradation of present image is surpassed first threshold value is evenly distributed in described each tonal gradation once more.
Wherein, described distribution method specifically may further comprise the steps:
Pixel count surpasses the residual pixel number of first threshold value in a, described each tonal gradation of calculating;
B, if the residual pixel number is 0, then finish, otherwise judge described residual pixel number whether greater than total progression of described each tonal gradation, if, execution in step c then, otherwise, execution in step d;
C, distribute identical pixel count, execution in step a then from described residual pixel, for described each tonal gradation;
D, obtain distributing step-length divided by described residual pixel number, according to this distribution step-length described residual pixel is dispensed in described each tonal gradation, then execution in step a with described total progression.
Concrete, described histogram equalization method specifically may further comprise the steps:
A, judge whether present image is single background image or the single background image of class, if then present image is not carried out histogram equalization, otherwise carry out subsequent process;
B, the pixel that pixel count in histogrammic each tonal gradation of present image is surpassed first threshold value are evenly distributed in described each tonal gradation once more;
C, the histogram of present image is carried out equalization;
D, obtain the grey scale mapping function, according to this grey scale mapping function present image is shone upon and obtain adjusted image according to the histogram after the step C equalization.
Wherein, judge whether it is that single background image or the single background image of class are judged in the following manner in the steps A:
If the ratio of all pixel counts of the pixel count of a certain tonal gradation and present image assert then that greater than second threshold value present image is single background image or the single background image of class in the present image histogram.
Wherein, described first threshold value obtains in the following manner:
At first, set dark threshold value and bright threshold value, calculate in the present image pixel count less than described dark threshold value, reach pixel count greater than described bright threshold value, if less than the ratio of the pixel count of described dark threshold value and all pixels greater than the 3rd threshold value, think that then present image is a dark background, if greater than the ratio of the pixel count of described bright threshold value and all pixels greater than the 3rd threshold value, think that then present image is bright background;
Then, according to formula:
Calculate described first threshold value; When assert that present image is dark background or bright background, then increase described first and regulate parameter.
Preferably, when assert that present image is dark background or bright background, described first regulates parameter regulates between 0.3～0.5, and when assert that not present image is dark background or bright background, described first regulates the value of parameter less than 0.3 and greater than 0.
Preferably, described dark threshold value value between 30～56; Described bright threshold value value between 180～220; Described the 3rd threshold value value between 2/5～3/5.
On the other hand, the present invention also proposes a kind of comparison of combined degree method of adjustment, and it also comprised the step that detail contrast is adjusted before described overall contrast set-up procedure, the input that the output of described detail contrast set-up procedure is adjusted as described overall contrast; And the step that described detail contrast is adjusted adopts the unsharp masking method to realize.
Wherein, described unsharp masking method specifically may further comprise the steps:
The first step, according to degradation model present image being degenerated to handle obtains degraded image;
In second step, whether the difference of judging original image and the described image of degenerating is less than the first sharpening threshold value, if then finish the detail contrast adjustment to present image; Otherwise, described difference be multiply by reinforcing coefficient, again with output described original image addition and that adjust as this detail contrast.
In addition, the described first step obtains degraded image to be passed through present image and low pass filter convolution, and the output after the convolution and the difference of original image are described degraded image; Described reinforcing coefficient is greater than 1; Described low pass filter is specially gauss low frequency filter, and its window size is 3 * 3.
The present invention can keep mean flow rate preferably thereby make by the image behind the histogram equalization, and strengthen the light and shade contrast owing to limit by the greatest gradient of first threshold value to the grey scale mapping function; In addition, therefore the present invention has avoided a large amount of calculating of partial equilibriumization because integral image is carried out histogram equalization.On the other hand, because the present invention combines histogram equalization and global contrast is adjusted with the unsharp masking method local detail contrast is adjusted, thereby avoid the shortcoming of single method (only part or overall contrast being adjusted), effectively raise contrast, make display effect more natural.
Description of drawings
Fig. 1 is the flow chart of an embodiment of contrast enhancement process proposed by the invention;
Fig. 2 is the flow chart of an embodiment of image histogram pixel assigning process.
Embodiment
Below in conjunction with accompanying drawing embodiments of the present invention are described in detail.
With reference to figure 1, illustrate the handling process of an embodiment of contrast enhancement process proposed by the invention.As shown in Figure 1, may further comprise the steps:
S100, input picture; That is, as present image.
S101, present image obtains degraded image after degradation model is handled; In one embodiment of the invention, described degraded image is realized by gauss low frequency filter, be the low-frequency component of the present image that obtains after present image and the gauss low frequency filter convolution, the window size of described gauss low frequency filter can be set to 3 * 3 sizes; In addition, described degraded image can also be by mean filter realization etc., and the present invention is not limited.
S102 removes the radio-frequency component that described degraded image composition obtains present image from original image; That is, behind the original image and described degraded image process subtracter with present image, just obtain the radio-frequency component of present image.
Whether S103, the radio-frequency component of judging present image greater than the first sharpening threshold value, if, execution in step S106 then, otherwise execution in step S104; The described first sharpening threshold value is predefined value, and in a preferred embodiment of the invention, its value is 3.
S104 utilizes reinforcing coefficient to strengthen the radio-frequency component of present image; That is, step S102 obtains multiplying each other with reinforcing coefficient β behind the radio-frequency component of present image, promptly increases β doubly; Described reinforcing coefficient β is greater than 1, in a preferred embodiment of the invention, and β value 1.5.
S105, HFS after the described enhancing and original image stack; That is, the two superposes by adder and obtains the adjusted output image of final details.
S106 judges whether present image is single background image or the single background image of class, if, execution in step S110 then, otherwise, execution in step S107;
In this step, judgement to single image or the single image of class realizes in the following manner: judge pixel count maximum in histogrammic each tonal gradation of present image, if the ratio of this maximum and all pixel numbers is greater than second threshold value, think that then present image is single background image or the single background image of class, otherwise be not.In a preferred embodiment of the invention, the described second threshold value value 0.5.
S107 carries out sub-distribution again according to first threshold value to present image histogram pixel; A specific embodiment of this step can be with reference to figure 2.
S108, histogram equalization; Because this step is utilized existing histogram equalization method, therefore no longer further set forth.
S109 calculates mapping function and calculates output image according to this mapping function; That is, step S108 histogram equalization is obtained the following formula of distribution function substitution obtains mapping function, and present image is shone upon, obtain output image according to this mapping function:
Wherein, n
1, n
2Be respectively the minimum value and the maximum of luminance signal tonal gradation; The histogram distribution that h (k) obtains for step S108; M is the pixel number of entire image.
S110 finishes; That is, end is to the details and the overall contrast adjustment of input picture.
Wherein, described original image is meant resulting image among the step S100.
With reference to figure 2, illustrate the handling process of an embodiment of image histogram pixel assigning process.As shown in Figure 2, may further comprise the steps:
S1071 calculates the residual pixel number that pixel count in each tonal gradation surpasses first threshold value; That is, in the present image histogram, set first threshold value, the pixel that surpasses described first threshold value in each tonal gradation is added up, determine its sum;
S1072 judges whether the residual pixel number is 0, if, execution in step S1076 then, otherwise, execution in step S1073.That is, whether the residual pixel quantity above first threshold value is 0 among the determining step S1071;
S1073 judges the residual pixel number whether greater than total progression of each tonal gradation, if, execution in step S1074 then, otherwise, execution in step S1075;
S1074 distributes the pixel count that equates for from described residual pixel described each tonal gradation; That is, each pixel that surpasses first threshold value among the step S1071 is distributed, it is assigned to each tonal gradation uniformly; For example, residual pixel is 160, tonal gradation add up to 50, then this moment, this step can be distributed 1 pixel to each tonal gradation, or 2 pixels, or 3 pixels; 3 pixels of preferred distribution, distributing the back residual pixel is 10;
This step finishes back execution in step S1071, promptly residual pixel is carried out uniform distribution after, once more the pixel count of current histogrammic each tonal gradation is judged, to determine whether that the residual pixel that surpasses described first threshold value is still arranged;
S1075, the dispensed step-length is dispensed to each tonal gradation with this step-length with residual pixel; That is, carry out this step and then represent the total progression of the quantity of residual pixel less than each tonal gradation, calculate a step-length residual pixel is carried out sub-distribution again this moment; It is described distribution step-length that total progression of each tonal gradation rounds the value that obtains after divided by the residual pixel sum;
This step finishes back execution in step S1071, after promptly residual pixel being distributed according to the distribution step-length, once more the pixel count of current histogrammic each tonal gradation is judged, to determine whether that the residual pixel that surpasses described first threshold value is still arranged;
S1075 finishes.That is, current histogrammic pixel redistribution process finishes.
Wherein, described first threshold value obtains in the following manner:
At first, set dark threshold value and bright threshold value, calculate in the present image pixel count less than described dark threshold value, reach pixel count greater than described bright threshold value, if less than the ratio of the pixel count of described dark threshold value and all pixels greater than the 3rd threshold value, think that then present image is a dark background, if greater than the ratio of the pixel count of described bright threshold value and all pixels greater than the 3rd threshold value, think that then present image is bright background;
Then, according to formula:
Calculate described first threshold value; When assert that present image is dark background or bright background, then increase described first and regulate parameter.
When assert that present image is dark background or bright background, described first regulates parameter regulates between 0.3～0.5, and for example 0.3,0.4,0.5 etc.; When assert that not present image is dark background or bright background, described first value of regulating parameter preferably can get 0.1 less than above-mentioned scope; Described dark threshold value can be between 30～56 value, for example can get 30,40,45,50,56 etc.; Value between described bright threshold value can be 180～220 for example can get 180,190,195,200,210,215,220 etc.; Described the 3rd threshold value can be between 2/5～3/5 value, for example can get 2/5,1/2,3/5 etc.
Above disclosed is a kind of preferred embodiment of the present invention only, can not limit the present invention's interest field certainly with this, and therefore the equivalent variations of doing according to claim of the present invention still belongs to the scope that the present invention is contained.
Claims (10)
1, a kind of contrast enhancement process, comprise the step that overall contrast is adjusted, this step adopts the histogram equalization method, it is characterized in that, described histogram equalization method limits the greatest gradient of resulting grey scale mapping function, and it is realized by following manner: the pixel that pixel count in histogrammic each tonal gradation of present image is surpassed first threshold value is evenly distributed in described each tonal gradation once more;
Wherein, described distribution method specifically may further comprise the steps:
Pixel count surpasses the residual pixel number of first threshold value in a, described each tonal gradation of calculating;
B, if the residual pixel number is 0, then finish, otherwise judge described residual pixel number whether greater than total progression of described each tonal gradation, if, execution in step c then, otherwise, execution in step d;
C, distribute identical pixel count, execution in step a then from described residual pixel, for described each tonal gradation;
D, obtain distributing step-length divided by described residual pixel number, according to this distribution step-length described residual pixel is dispensed in described each tonal gradation, then execution in step a with described total progression.
2, method according to claim 1 is characterized in that, described histogram equalization method specifically may further comprise the steps:
A, judge whether present image is single background image or the single background image of class, if, then present image is not carried out histogram equalization, otherwise, carry out subsequent process;
B, the pixel that pixel count in histogrammic each tonal gradation of present image is surpassed first threshold value are evenly distributed in described each tonal gradation once more;
C, the histogram of present image is carried out equalization;
D, obtain the grey scale mapping function, according to this grey scale mapping function present image is shone upon and obtain adjusted image according to the histogram after the step C equalization.
3, method according to claim 2 is characterized in that, judges whether it is that single background image or the single background image of class are judged in the following manner in the steps A:
If the ratio of all pixel counts of the pixel count of a certain tonal gradation and present image assert then that greater than second threshold value present image is single background image or the single background image of class in the present image histogram.
4, method according to claim 1 is characterized in that, described first threshold value obtains in the following manner:
At first, set dark threshold value and bright threshold value, calculate in the present image pixel count less than described dark threshold value, reach pixel count greater than described bright threshold value, if less than the ratio of the pixel count of described dark threshold value and all pixels greater than the 3rd threshold value, think that then present image is a dark background, if greater than the ratio of the pixel count of described bright threshold value and all pixels greater than the 3rd threshold value, think that then present image is bright background;
Then, according to formula:
Calculate described first threshold value; When assert that present image is dark background or bright background, then increase described first and regulate parameter.
5, method according to claim 4, it is characterized in that, when assert that present image is dark background or bright background, described first regulates parameter regulates between 0.3～0.5, when assert that not present image is dark background or bright background, described first regulates the value of parameter less than 0.3 and greater than 0.
6, method according to claim 5 is characterized in that, described dark threshold value value between 30～56; Described bright threshold value value between 180～220; Described the 3rd threshold value value between 2/5～3/5.
7, method according to claim 1 is characterized in that, also comprises the step that detail contrast is adjusted in this method before described overall contrast set-up procedure, the input that the output of described detail contrast set-up procedure is adjusted as described overall contrast; And the step that described detail contrast is adjusted adopts the unsharp masking method to realize.
8, method according to claim 7 is characterized in that, described unsharp masking method specifically may further comprise the steps:
The first step, according to degradation model present image being degenerated to handle obtains degraded image;
In second step, whether the difference of judging original image and described degraded image is less than the first sharpening threshold value, if then finish the detail contrast adjustment to present image; Otherwise, described difference be multiply by reinforcing coefficient, again with described original image addition after, the output of adjusting as this detail contrast.
9, method according to claim 8 is characterized in that, the described first step obtains degraded image and is the low-frequency component with the present image after present image and the low pass filter convolution, and described reinforcing coefficient is greater than 1.
10, method according to claim 9 is characterized in that, described low pass filter is a gauss low frequency filter, and its window size is 3 * 3.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102096909A (en) * | 2010-12-30 | 2011-06-15 | 东北大学 | Improved unsharp masking image reinforcing method based on logarithm image processing model |
Families Citing this family (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101715143B (en) * | 2008-10-07 | 2011-09-14 | 华为技术有限公司 | Method, device and system of self-adaptive quantization and self-adaptive inverse quantization |
| CN102456222B (en) * | 2010-10-29 | 2013-12-04 | 深圳迈瑞生物医疗电子股份有限公司 | Method and device for organized equalization in image |
| CN102194220B (en) * | 2011-05-10 | 2012-11-28 | 西安理工大学 | Image enhancement method based on combination of sharpening strength and gray scale distribution |
| CN102750673A (en) * | 2011-11-30 | 2012-10-24 | 新奥特（北京）视频技术有限公司 | Method for improving image contrast |
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| CN110070508B (en) * | 2019-04-23 | 2020-11-10 | 西安交通大学 | Unsharp enhancement method based on threshold value and linear mapping |
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-
2007
- 2007-12-25 CN CNB2007101163612A patent/CN100563312C/en active Active
Non-Patent Citations (2)
| Title |
|---|
| 基于直方图均衡与反锐化掩模的DR图像增强. 尚杨等.2007中国生物医学工程联合学术年会论文集(上册). 2007 |
| 基于直方图均衡与反锐化掩模的DR图像增强. 尚杨等.2007中国生物医学工程联合学术年会论文集(上册). 2007 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102096909A (en) * | 2010-12-30 | 2011-06-15 | 东北大学 | Improved unsharp masking image reinforcing method based on logarithm image processing model |
| CN102096909B (en) * | 2010-12-30 | 2012-07-04 | 东北大学 | Improved unsharp masking image reinforcing method based on logarithm image processing model |
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