CN110400260A - Image processing method and device - Google Patents
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
- G06T5/94—Dynamic range modification of images or parts thereof based on local image properties, e.g. for local contrast enhancement
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Abstract
The present invention provides a kind of image processing method and device, by the way that flat region extension and adaptive flat region pixel detection are added in CLAHE algorithm, and the amplitude of the brightness histogram of rectangular area where modifying flat region pixel is particular value, so that amplitude is that treated that contrast remains unchanged by histogram equalization for the pixel of particular value, the problems such as so as to preferably inhibit noise amplification while adaptively enhancing Image Warping and brightness and image is avoided color range and camber line occur.
Description
Technical field
The present invention relates to technical field of image processing more particularly to a kind of image processing methods and device.
Background technique
In mobile phone use process, user is frequently necessary to watch mobile phone screen under strong environment light, such as outdoor strong
Strong sunlight or indoor strong light, strong due to environment light, the environment light of mobile phone screen reflection is more, leads to user
The mobile phone screen observed shows the visibility decline of content.At this moment, user is often that the backlight illumination of mobile phone screen is turned up,
This problem can be alleviated in many cases, but the highest brightness value of some mobile phone screens is lower, even if it is bright to improve backlight
It spends to maximum value, however it remains not the case where not seeing image, and increase screen backlight brightness, mobile telephone power consumption can be made significantly to increase
Add, reduces stand-by time.And pass through the real time image processing of local tone mapping (Local tone mapping, LTM),
According to ambient light intensity, image pixel value is adaptively adjusted, Image Warping and brightness can be promoted, enhances image in hand
Visibility on machine screen makes up the problem that screen backlight is inadequate and power consumption is big, this is the readable function of the sunlight of mobile phone.Various
In real time in the tone-mapping algorithm of part, self-adapting histogram equilibrium (the Contrast Limited Adaptive of contrast is limited
Histogram Equalization, CLAHE) algorithm has the advantages that effect is good, versatile and hardware costs is lower, it is most
Common tone-mapping algorithm local in real time, principle is to divide the image into several rectangular tiles, is distinguished each rectangular tiles
Histogram equalization is done to realize that local contrast is promoted, carrys out smooth each piece of processing result finally by interpolation, it is complicated to reduce calculating
Degree.
In the implementation of the present invention, inventor's discovery at least has the following technical problems in the prior art:
The most important feature of CLAHE algorithm is, limits contrast enlargement range for each rectangle cell domain, is used to gram
Clothes excessively amplify the problem of noise, but since the image sources that mobile phone screen is shown are complicated, quality is different, therefore in order to be applicable in
The image of various noise levels sets very high so generally contrast will not be promoted amplitude, in order to avoid in enhancing picture contrast
With the problems such as color range and camber line occur in the amplification of generation noise and image while brightness.And in actual use when environment light is non-
When Chang Qianglie, Image Warping and brightness corresponding must be greatly increased, and being just able to satisfy user can to screen
The requirement that diopter is promoted.It can be seen that at this moment CLAHE algorithm is difficult to balance the relationship between contrast amplification and noise suppressed,
For example, picture contrast and luminance raising have arrived customer satisfaction system degree, but obvious noise may be will appear simultaneously, image goes out
The problems such as existing color range and camber line.
Summary of the invention
Image treating and device provided by the invention, can adaptively enhancing Image Warping and brightness it is same
When preferably inhibit noise amplification and avoid image from the problems such as color range and camber line occur.
In a first aspect, the present invention provides a kind of image processing method, comprising:
The pixel gradient value of each pixel in luminance component image to be processed is calculated, and counts the picture for being less than first threshold T1
The corresponding histogram of gradients of the pixel of plain gradient value, and the luminance component image to be processed is counted according to the histogram of gradients
Noise level T2；
The luminance component image to be processed is divided into multiple rectangular areas, the first brightness for counting each rectangular area is straight
Fang Tu, determine in each rectangular area be made of the pixel of the pixel gradient value less than the noise level T2 it is first flat
Area；
Flat region extension process is carried out to each first flat region using low-pass filter and obtains corresponding second flat region,
And the brightness histogram of each second flat region is counted, the brightness histogram of second flat region is calculated for each brightness value
With the amplitude ratio of the brightness histogram of rectangular area where second flat region, the Amplitude Ratio for being greater than third threshold value T3 is determined
The corresponding brightness value of value, and set the pixel where second flat region in rectangular area with the corresponding brightness value to
Flat region pixel；
The minimum effective breadth H1 for calculating the first brightness histogram of each rectangular area, will be where the flat region pixel
The amplitude of the brightness histogram of rectangular area is uniformly revised as H1, and the difference of amplitude initial value and H1 before modification is added up
The peak position of first brightness histogram of rectangular area where being added to after summation, to obtain the second brightness histogram of each rectangle
Figure；
Adaptive equalization processing is carried out using second brightness histogram of the CLAHE algorithm to each rectangle, it is described to obtain
The final brightness value of each pixel in luminance component image to be processed.
Second aspect, the present invention provide a kind of image processing apparatus, comprising:
Noise level statistical module, for calculating the pixel gradient value of each pixel in luminance component image to be processed, and
The corresponding histogram of gradients of pixel of pixel gradient value of the statistics less than first threshold T1, and counted according to the histogram of gradients
The noise level T2 of the luminance component image to be processed；
First brightness histogram computing module, for the luminance component image to be processed to be divided into multiple rectangular areas,
Count the first brightness histogram of each rectangular area；
First flat region determining module, for determining in each rectangular area by the pixel ladder less than the noise level T2
First flat region of the pixel composition of angle value；
Second flat region and its brightness histogram determining module, for using low-pass filter to each first flat region into
Row flat region extension process obtains corresponding second flat region, and counts the brightness histogram of each second flat region；
Flat region pixel determining module, for for each brightness value calculate the brightness histogram of second flat region with
The amplitude ratio of the brightness histogram of rectangular area where second flat region, determines the amplitude ratio for being greater than third threshold value T3
Corresponding brightness value, and set flat for the pixel where second flat region in rectangular area with the corresponding brightness value
Smooth area's pixel；
Magnitude computation module, the minimum effective breadth H1 of the first brightness histogram for calculating each rectangular area；
Second brightness histogram computing module, for by the brightness histogram of rectangular area where the flat region pixel
Amplitude is uniformly revised as H1, and is added to place rectangular area after the difference of amplitude initial value and H1 before modification is carried out accumulative summation
The first brightness histogram peak position, to obtain the second brightness histogram of each rectangle；
Adaptive balance module, it is adaptive for being carried out using second brightness histogram of the CLAHE algorithm to each rectangle
Equilibrium treatment, to obtain the final brightness value of each pixel in the luminance component image to be processed.
Image processing method and device provided in an embodiment of the present invention, compared with prior art, by CLAHE algorithm
Flat region extension and adaptive flat region pixel detection is added, and modifies the brightness histogram of flat region pixel place rectangular area
Amplitude be particular value so that amplitude is that treated that contrast remains unchanged by histogram equalization for the pixel of particular value, from
And it can preferably inhibit noise amplification while adaptively enhancing Image Warping and brightness and image is avoided to go out
The problems such as existing color range and camber line.In addition, due to adaptive noise inhibitory effect, it is thus possible to be suitable for contrast and be promoted by force
Strong application scenarios, and implementation complexity is low, is suitble to hardware realization and the processing of mobile phone real-time display.
Detailed description of the invention
Fig. 1 is the flow chart of one embodiment of the invention image processing method；
Fig. 2 is the structural schematic diagram of one embodiment of the invention image processing apparatus.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is only
It is only a part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill
Personnel's every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
The present invention provides a kind of image processing method, as shown in Figure 1, which comprises
S11, the pixel gradient value for calculating each pixel in luminance component image to be processed, and count and be less than first threshold T1
Pixel gradient value the corresponding histogram of gradients of pixel, and the brightness of image to be processed is counted according to the histogram of gradients
The noise level T2 of component.
S12, the luminance component image to be processed is divided into multiple rectangular areas, count each rectangular area first is bright
Spend histogram, determine in each rectangular area be made of the pixel of the pixel gradient value less than the noise level T2 it is first flat
Smooth area.
S13, carrying out flat region extension process to each first flat region using low-pass filter, to obtain corresponding second flat
Smooth area, and the brightness histogram of each second flat region is counted, the brightness of second flat region is calculated for each brightness value
The amplitude ratio of the brightness histogram of rectangular area, determines greater than third threshold value T3's where histogram and second flat region
The corresponding brightness value of amplitude ratio, and the pixel that will there is the corresponding brightness value where second flat region in rectangular area
It is set as flat region pixel.
The principle of flat region extension process is as follows: for example, the brightness range of flat region is 0-255, flat region after upper step
Brightness range be 64-128, it is contemplated that being in the pixel of flat area edge, belonging to flat region in quantity and not belonging to
Quantity in flat region is close, for example the pixel that brightness is 64 counts totally 10 on rectangle region brightness histogram, wherein passing through
Previous step judges that the quantity for belonging to flat region is 5, and the quantity in non-flat forms area is also 5, is judged as flat region
Pixel quantity is not dominant, and subsequent judgment method (ratio 5/10) may be such that 64 pixels for being by brightness are judged to
Non-flat forms area pixel influences algorithm in the effect of flat area edge.In order to avoid such situation, pass through low-pass filtering (such as 5
Rank FIR low pass filter), it can adaptively force down pixels statistics of the brightness histogram at the peak value of flat district center
Value, and the pixels statistics value complement got off will be subtracted and repaid on edge pixel statistical value, for example, make on the brightness histogram of flat region,
The statistical value that brightness is 64 increases to 8 from 5, and ratio becomes being 8/10, and judgment method subsequent in this way will have more high probability will be bright
It spends 64 pixels and is judged as that flat region pixel is handled.
S14, calculate each rectangular area the first brightness histogram minimum effective breadth H1, by the flat region pixel
The amplitude of the brightness histogram of place rectangular area is uniformly revised as H1, and the difference of amplitude initial value and H1 before modification is carried out
The peak position of first brightness histogram of rectangular area where being added to after accumulative summation, to obtain the second brightness of each rectangle
Histogram；
S15, adaptive equalization processing is carried out using second brightness histogram of the CLAHE algorithm to each rectangle, to obtain
The final brightness value of each pixel in the luminance component image to be processed.
Subsequent processing is handled according to CLAHE algorithm flow, is only replaced with the second brightness histogram of each rectangle
The original brightness statistic histogram of CLAHE algorithm.Its process are as follows: to a each rectangular area, on new brightness histogram successively
Degree of comparing clipping and with redistribution operate, generate contrast clipping brightness histogram；Then, it carries out at histogram equalization
Reason generates brightness mapping (tone mapping) table of each rectangular area；Finally, using adjacent four regions to each pixel
Brightness mapping table find corresponding four mapping values respectively, then the distance with pixel accordingly to four rectangular areas center makes
Insert the final brightness value of each pixel with bilinear interpolation.
Image processing method provided in an embodiment of the present invention is compared with prior art, flat by being added in CLAHE algorithm
Smooth area's extension and adaptive flat region pixel detection, and modify the amplitude of the brightness histogram of flat region pixel place rectangular area
For particular value, so that the pixel that amplitude is particular value passes through histogram equalization, treated, and contrast is remained unchanged, so as to
Preferably inhibit noise amplification while adaptively enhancing Image Warping and brightness and image is avoided color range occur
And the problems such as camber line, in addition, due to adaptive noise inhibitory effect, it is thus possible to promote strong answer suitable for contrast
With scene, and implementation complexity is low, is suitble to hardware realization and the processing of mobile phone real-time display.
Optionally, the pixel gradient value for calculating each pixel in luminance component image to be processed includes:
The horizontal gradient value and vertical gradient value of each pixel in the luminance component image to be processed are calculated, and will be described
Horizontal gradient value is added to obtain the pixel gradient value with the vertical gradient value.
Optionally, the noise level T2 packet that the luminance component image to be processed is counted according to the histogram of gradients
It includes:
If (Gmax× 2 < T1), T2=Gmax×2；Otherwise, T2=T1；
Wherein, GmaxFor the pixel gradient value of each pixel in the luminance component image to be processed.
Optionally, the minimum effective breadth H1 of the brightness histogram for calculating each rectangular area is real in the following manner
It is existing:
H1=(M × N)/(Vmax-Vmin), wherein M and N is respectively that the rectangular area is long and wide, Vmax and Vmin difference
It is the brightness maxima and minimum value of the rectangular area.
As shown in Fig. 2, the embodiment of the present invention provides a kind of image processing apparatus, described device includes:
Noise level statistical module, for calculating the pixel gradient value of each pixel in luminance component image to be processed, and
The corresponding histogram of gradients of pixel of pixel gradient value of the statistics less than first threshold T1, and counted according to the histogram of gradients
The noise level T2 of the luminance component image to be processed；
First brightness histogram computing module, for the luminance component image to be processed to be divided into multiple rectangular areas,
Count the first brightness histogram of each rectangular area；
First flat region determining module, for determining in each rectangular area by the pixel ladder less than the noise level T2
First flat region of the pixel composition of angle value；
Second flat region and its brightness histogram determining module, for using low-pass filter to each first flat region into
Row flat region extension process obtains corresponding second flat region, and counts the brightness histogram of each second flat region；
Flat region pixel determining module, for for each brightness value calculate the brightness histogram of second flat region with
The amplitude ratio of the brightness histogram of rectangular area where second flat region, determines the amplitude ratio for being greater than third threshold value T3
Corresponding brightness value, and set flat for the pixel where second flat region in rectangular area with the corresponding brightness value
Smooth area's pixel；
Magnitude computation module, the minimum effective breadth H1 of the first brightness histogram for calculating each rectangular area；
Second brightness histogram computing module, for by the brightness histogram of rectangular area where the flat region pixel
Amplitude is uniformly revised as H1, and is added to place rectangular area after the difference of amplitude initial value and H1 before modification is carried out accumulative summation
The first brightness histogram peak position, to obtain the second brightness histogram of each rectangle；
Adaptive balance module, it is adaptive for being carried out using second brightness histogram of the CLAHE algorithm to each rectangle
Equilibrium treatment, to obtain the final brightness value of each pixel in the luminance component image to be processed.
Image processing apparatus provided in an embodiment of the present invention is compared with prior art, flat by being added in CLAHE algorithm
Smooth area's extension and adaptive flat region pixel detection, and modify the amplitude of the brightness histogram of flat region pixel place rectangular area
For particular value, so that the pixel that amplitude is particular value passes through histogram equalization, treated, and contrast is remained unchanged, so as to
Preferably inhibit noise amplification while adaptively enhancing Image Warping and brightness and image is avoided color range occur
And the problems such as camber line, in addition, due to adaptive noise inhibitory effect, it is thus possible to promote strong answer suitable for contrast
With scene, and implementation complexity is low, is suitble to hardware realization and the processing of mobile phone real-time display.
Optionally, the noise level statistical module includes gradient pixel value computing unit, and the gradient pixel value calculates
Unit, for calculating the horizontal gradient value and vertical gradient value of each pixel in the luminance component image to be processed, and by institute
Horizontal gradient value is stated to be added to obtain the pixel gradient value with the vertical gradient value.
Optionally, the noise level statistical module includes noise level computing unit, the noise level computing unit,
For obtaining noise level T2 in the following manner: if (Gmax× 2 < T1), T2=Gmax×2；Otherwise, T2=T1；Wherein,
GmaxFor the pixel gradient value of each pixel in the luminance component image to be processed.
Optionally, the magnitude computation module obtains the minimum of the brightness histogram of each rectangular area in the following manner
Effective breadth H1:
H1=(M × N)/(Vmax-Vmin), wherein M and N is respectively that the rectangular area is long and wide, Vmax and Vmin difference
It is the brightness maxima and minimum value of the rectangular area.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the program can be stored in a computer-readable storage medium
In, the program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (Random Access
Memory, RAM) etc..
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of by those familiar with the art, all answers
It is included within the scope of the present invention.Therefore, protection scope of the present invention should be subject to the protection scope in claims.
Claims (8)
1. a kind of image processing method characterized by comprising
The pixel gradient value of each pixel in luminance component image to be processed is calculated, and counts the pixel ladder less than first threshold T1
The corresponding histogram of gradients of the pixel of angle value, and making an uproar for the luminance component image to be processed is counted according to the histogram of gradients
The horizontal T2 of sound；
The luminance component image to be processed is divided into multiple rectangular areas, counts the first brightness histogram of each rectangular area
Figure determines the first flat region being made of in each rectangular area the pixel of the pixel gradient value less than the noise level T2；
Flat region extension process is carried out to each first flat region using low-pass filter and obtains corresponding second flat region, and is united
The brightness histogram for counting each second flat region calculates brightness histogram and the institute of second flat region for each brightness value
The amplitude ratio of the brightness histogram of rectangular area where stating the second flat region, determines the amplitude ratio greater than third threshold value T3
Corresponding brightness value, and set flat for the pixel where second flat region in rectangular area with the corresponding brightness value
Area's pixel；
The minimum effective breadth H1 for calculating the first brightness histogram of each rectangular area, by rectangle where the flat region pixel
The amplitude of the brightness histogram in region is uniformly revised as H1, and the difference of amplitude initial value and H1 before modification is carried out accumulative summation
The peak position of first brightness histogram of rectangular area where being added to afterwards, to obtain the second brightness histogram of each rectangle；
Adaptive equalization processing is carried out using second brightness histogram of the CLAHE algorithm to each rectangle, it is described wait locate to obtain
Manage the final brightness value of each pixel in luminance component image.
2. the method according to claim 1, wherein described calculate each pixel in luminance component image to be processed
Pixel gradient value include:
Calculate the horizontal gradient value and vertical gradient value of each pixel in the luminance component image to be processed, and by the level
Gradient value is added to obtain the pixel gradient value with the vertical gradient value.
3. the method according to claim 1, wherein described count described to be processed according to the histogram of gradients
The noise level T2 of luminance component image includes:
If (Gmax× 2 < T1), T2=Gmax×2；Otherwise, T2=T1；
Wherein, GmaxFor the pixel gradient value of each pixel in the luminance component image to be processed.
4. the method according to claim 1, wherein the brightness histogram for calculating each rectangular area is most
Low effective breadth H1 is accomplished by the following way:
H1=(M × N)/(Vmax-Vmin), wherein M and N is respectively that the rectangular area is long and wide, and Vmax and Vmin are institute respectively
State the brightness maxima and minimum value of rectangular area.
5. a kind of image processing apparatus characterized by comprising
Noise level statistical module for calculating the pixel gradient value of each pixel in luminance component image to be processed, and counts
The corresponding histogram of gradients of pixel of pixel gradient value less than first threshold T1, and according to histogram of gradients statistics
The noise level T2 of luminance component image to be processed；
First brightness histogram computing module is counted for the luminance component image to be processed to be divided into multiple rectangular areas
First brightness histogram of each rectangular area；
First flat region determining module, for determining the pixel gradient value in each rectangular area by being less than the noise level T2
Pixel composition the first flat region；
Second flat region and its brightness histogram determining module, it is flat for being carried out using low-pass filter to each first flat region
Smooth area's extension process obtains corresponding second flat region, and counts the brightness histogram of each second flat region；
Flat region pixel determining module, for for each brightness value calculate the brightness histogram of second flat region with it is described
The amplitude ratio of the brightness histogram of rectangular area where second flat region, determines pair of the amplitude ratio greater than third threshold value T3
Brightness value is answered, and sets flat region for the pixel where second flat region in rectangular area with the corresponding brightness value
Pixel；
Magnitude computation module, the minimum effective breadth H1 of the first brightness histogram for calculating each rectangular area；
Second brightness histogram computing module, for by the amplitude of the brightness histogram of rectangular area where the flat region pixel
It is uniformly revised as H1, and the difference of amplitude initial value and H1 before modification is carried out the of rectangular area where being added to after accumulative summation
The peak position of one brightness histogram, to obtain the second brightness histogram of each rectangle；
Adaptive balance module, for carrying out adaptive equalization using second brightness histogram of the CLAHE algorithm to each rectangle
Processing, to obtain the final brightness value of each pixel in the luminance component image to be processed.
6. device according to claim 5, which is characterized in that the noise level statistical module includes gradient pixel value meter
Calculate unit, the gradient pixel value computing unit, for calculating the level of each pixel in the luminance component image to be processed
Gradient value and vertical gradient value, and the horizontal gradient value is added to obtain the pixel gradient with the vertical gradient value
Value.
7. device according to claim 5, which is characterized in that the noise level statistical module includes that noise level calculates
Unit, the noise level computing unit, for obtaining noise level T2 in the following manner: if (Gmax× 2 < T1), T2=
Gmax×2；Otherwise, T2=T1；Wherein, GmaxFor the pixel gradient value of each pixel in the luminance component image to be processed.
8. device according to claim 5, which is characterized in that the magnitude computation module obtains each in the following manner
The minimum effective breadth H1 of the brightness histogram of rectangular area:
H1=(M × N)/(Vmax-Vmin), wherein M and N is respectively that the rectangular area is long and wide, and Vmax and Vmin are institute respectively
State the brightness maxima and minimum value of rectangular area.
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| CN112967207A (en) * | 2021-04-23 | 2021-06-15 | 北京恒安嘉新安全技术有限公司 | Image processing method and device, electronic equipment and storage medium |
| CN112967207B (en) * | 2021-04-23 | 2024-04-12 | 北京恒安嘉新安全技术有限公司 | Image processing method and device, electronic equipment and storage medium |
| CN113077404A (en) * | 2021-05-27 | 2021-07-06 | 杭州微帧信息科技有限公司 | Method for improving image contrast |
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