CN107403412A - Image processing method and apparatus for carrying out the method - Google Patents
Image processing method and apparatus for carrying out the method Download PDFInfo
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Classifications
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- G06T5/70—
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/71—Circuitry for evaluating the brightness variation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/44—Receiver circuitry for the reception of television signals according to analogue transmission standards
- H04N5/57—Control of contrast or brightness
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/64—Circuits for processing colour signals
- H04N9/646—Circuits for processing colour signals for image enhancement, e.g. vertical detail restoration, cross-colour elimination, contour correction, chrominance trapping filters
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20172—Image enhancement details
- G06T2207/20192—Edge enhancement; Edge preservation
Abstract
The present invention relates to a kind of image processing method and apparatus for carrying out the method.Included according to the image processing apparatus of exemplary embodiment：Color notation conversion space portion, brightness (Y) composition is extracted from input picture by converting the color space of input picture；Wavelet transformation portion, wavelet transformation is carried out to the input picture of luminance components and generates LL subgraphs, LH subgraphs, HL subgraphs and HH subgraphs；First image enhancement portion, LL subgraphs are received from wavelet transformation portion, and improve the contrast of LL subgraphs；And the second image enhancement portion, LH subgraphs, HL subgraphs and HH subgraphs are received from wavelet transformation portion, and perform the improvement of contrast and the removal of noise for LH subgraphs, HL subgraphs and HH subgraphs.
Description
Technical field
Embodiments of the invention are related to a kind of image processing techniques.
Background technology
With the popularization for the mobile terminal for possessing camera, the image captured by camera is applied not only to security protection and monitoring, also
For shooting the daily life of individual and by its shared various purposes.However, at night or illuminate weaker interior etc.
The readability of the image shot under low-light (level) environment will reason low key tone (tone) or image quality deterioration caused by noise and
Reduce.In order to improve the image quality of the image shot under low-light (level) environment, the improvement of contrast and the removal of noise need to be carried out, so
And in the prior art, there is can not be simultaneously and the problem of the processing is performed quickly.
[prior art literature]
[patent document]
(patent document 01) Korean granted patent publication the 10-1141844th (2012.05.07)
The content of the invention
The purpose of embodiments of the invention is to provide a kind of for the contrast of the image photographed under low-light (level) environment
The image processing method that the improvement of degree and the removal of noise can rapidly process simultaneously and the dress for performing this method
Put.
Included according to the image processing apparatus of one embodiment of the invention：Color notation conversion space portion, by converting input figure
The color space of picture and from the input picture extract brightness (Y) composition；Wavelet transformation portion, the input to the luminance components
Image carries out wavelet transformation and generates LL subgraphs, LH subgraphs, HL subgraphs and HH subgraphs；First image enhancement portion,
The LL subgraphs are received from the wavelet transformation portion, and improve the contrast of the LL subgraphs；And second image enhancement
Portion, LH subgraphs, HL subgraphs and the HH subgraphs are received from the wavelet transformation portion, and perform and be directed to the LH subgraphs
The improvement of contrast and the removal of noise of picture, HL subgraphs and HH subgraphs.
The improvement of the contrast of the LL subgraphs and the contrast of the LH subgraphs, HL subgraphs and HH subgraphs
Improvement and the removal of noise can be performed in parallel in described first image improvement portion and the second image enhancement portion.
Described image processing unit can also include：Standardization Sector, to being extracted by the color notation conversion space portion
The luminance components are standardized and the input picture of the normalised luminance components are delivered into the wavelet transformation
Portion.
The Standardization Sector can be standardized by following mathematical expressions 1 to the luminance components extracted.
(mathematical expression 1)
Here, YnorRepresent normalised luminance components；YmaxRepresent the maximum of luminance components extracted；YminTable
Show the minimum value of the luminance components extracted.
The second image enhancement portion can be in the LH subgraphs, HL subgraphs and HH subgraphs according to wavelet systems
Numerical value and detect strong edge, weak edge and noise, and keep or modification correspond to detect strong edge, weak edge and
The wavelet coefficient values of noise, so as to perform the improvement of the contrast for the LH subgraphs, HL subgraphs and HH subgraphs
And the removal of noise.
The second image enhancement portion can be detected the strong edge, weak edge and be made an uproar by following mathematical expressions 2
Sound.
(mathematical expression 2)
mean(wI, j)≥kσ；Strong edge
mean(wI, j) ＜ k σ, max >=k σ；Weak edge
mean(wI, j) ＜ k σ, max ＜ k σ；Noise
Here, wi,jRepresent the small echo of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Coefficient；mean(wi,j) represent each LH subgraphs, HL subgraphs and HH subgraphs wavelet coefficient (w) local average；
Max represents the maximum of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs；K represents variable, is adjustable
Value；σ represents the standard deviation of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs.
The second image enhancement portion can calculate the standard deviation by following mathematical expressions 3.
(mathematical expression 3)
Here, MAD represents that the median of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs is definitely inclined
Difference.
The second image enhancement portion can keep or change the strong side with the detection by following mathematical expressions 4
Edge, weak edge and wavelet coefficient values corresponding to noise.
(mathematical expression 4)
Here, wi,jRepresent the small echo of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Coefficient；w'i,jRepresent the wavelet systems of the modification of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Number；K, p represents variable, is adjustable value；σ represents the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs
Standard deviation.
Described image processing unit can also include：Inverse wavelet transform portion, by the LL subgraphs, LH subgraphs, HL
Image and the image that HH subgraphs inverse wavelet transform is luminance components.
Described image processing unit is based on the luminance components extracted from the color notation conversion space portion and from described against small
The luminance components that wave conversion portion obtains adjust the color of the input picture, so as to output result image.
The color adjustment portion can adjust the color of the input picture by following mathematical expressions 5.
(mathematical expression 5)
Here, Y represents the luminance components from the extraction of color notation conversion space portion；YeRepresent from the bright of inverse wavelet transform portion acquisition
Spend composition；[R, G, B] represents the RGB compositions of input picture；[R', G', B'] represents the RGB compositions of result images.
Included according to the computing device of one embodiment of the invention：More than one processor；Memory；It is more than one
Program, one program storage above perform in the memory, and by one processor above, and described one
Program more than individual includes：For to input picture carry out wavelet transformation and generate LL subgraphs, LH subgraphs, HL subgraphs with
And the instruction of HH subgraphs；For the instruction for the contrast for improving the LL subgraphs；For performing to the LH subgraphs, HL
The improvement of the contrast of subgraph and HH subgraphs and the instruction of the removal of noise.
The improvement of the contrast of the LL subgraphs and the contrast of the LH subgraphs, HL subgraphs and HH subgraphs
Improvement and the removal of noise can be executed in parallel in the computing device.
For performing the improvement of contrast and the removal of noise of the LH subgraphs, HL subgraphs and HH subgraphs
Instruction can include following instruction：For in the LH subgraphs, HL subgraphs and HH subgraphs according to wavelet systems
Numerical value and the instruction for detecting strong edge, weak edge and noise；And for strong with the detection by keeping or changing
Edge, weak edge and wavelet coefficient values corresponding to noise and perform for the LH subgraphs, HL subgraphs and HH subgraphs
The improvement of the contrast of picture and the removal of noise.
Program more than one can include：For detecting the strong edge, weak side by following mathematical expressions 6
The instruction of edge and noise.
(mathematical expression 6)
mean(wI, j)≥kσ；Strong edge
mean(wI, j) ＜ k σ, max >=k σ；Weak edge
mean(wI, j) ＜ k σ, max ＜ k σ；Noise
Here, wi,jRepresent the small echo of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Coefficient；mean(wi,j) represent each LH subgraphs, HL subgraphs and HH subgraphs wavelet coefficient (w) local average；
Max represents the maximum of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs；K represents variable, is adjustable
Value；σ represents the standard deviation of each LH subgraphs, HL subgraphs and the wavelet coefficient in HH subgraphs.
Program more than one can include being used to calculate the finger of the standard deviation by following mathematical expressions 7
Order.
(mathematical expression 7)
Here, MAD represents that the median of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs is definitely inclined
Difference.
Program more than one can include being used to keep or change and the inspection by following mathematical expressions 8
The instruction of the strong edge of survey, weak edge and wavelet coefficient values corresponding to noise.
(mathematical expression 8)
Here, wi,jRepresent the small echo of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Coefficient；w'i,jRepresent the wavelet systems of the modification of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Number；K, p represents variable, is adjustable value；σ represents the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs
Standard deviation.
The steps is included according to the image processing method of one embodiment of the invention：In image processing apparatus, lead to
Cross the color space of conversion input picture and extract luminance components from the input picture；In described image processing unit,
Wavelet transformation is carried out to the input picture of the luminance components and generates LL subgraphs, LH subgraphs, HL subgraphs and HH
Image；In described image processing unit, improve the contrast of the LL subgraphs；And in described image processing unit,
Perform the improvement of contrast and the removal of noise for the LH subgraphs, HL subgraphs and HH subgraphs.
In described image processing unit, the step of being performed in parallel improving the contrast of the LL subgraphs and hold
The step of removal of improvement and noise of the hand-manipulating of needle to the contrast of the LH subgraphs, HL subgraphs and HH subgraphs.
After performing the step of luminance components are extracted from the input picture, the steps can also be included：Institute
State in image processing apparatus, the luminance components extracted by the color notation conversion space portion are standardized.
, can be by following mathematical expressions and to described in described image processing unit in the step of standardization
The luminance components of extraction are standardized.
(mathematical expression 9)
Here, YnorRepresent normalised luminance components；YmaxRepresent the maximum of luminance components extracted；YminTable
Show the minimum value of the luminance components extracted.
Perform the improvement of contrast and the removal of noise for the LH subgraphs, HL subgraphs and HH subgraphs
The step of can include the steps：In described image processing unit, in the LH subgraphs, HL subgraphs and HH
Strong edge, weak edge and noise are detected in image according to wavelet coefficient values；In described image processing unit, keep or
Modification corresponds to the wavelet coefficient values of strong edge, weak edge and noise detected, so as to perform for the LH subgraphs,
The improvement of the contrast of HL subgraphs and HH subgraphs and the removal of noise.
In the step of detecting the strong edge, weak edge and noise, it can be detected by following mathematical expressions 10
The strong edge, weak edge and noise.
(mathematical expression 10)
mean(wI, j)≥kσ；Strong edge
mean(wI, j) ＜ k σ, max >=k σ；Weak edge
mean(wI, j) ＜ k σ, max ＜ k σ；Noise
Here, wi,jRepresent the small echo of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Coefficient；mean(wi,j) represent each LH subgraphs, HL subgraphs and HH subgraphs wavelet coefficient (w) local average；
Max represents the maximum of each LH subgraphs, HL subgraphs and the wavelet coefficient in HH subgraphs；K represents variable, is adjustable
The value of section；σ represents the standard deviation of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs.
In the step of detecting the strong edge, weak edge and noise, it can be calculated by following mathematical expressions 11
The standard deviation
(mathematical expression 11)
Here, MAD represents that the median of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs is definitely inclined
Difference.
Performing the improvement of contrast and going for noise for the LH subgraphs, HL subgraphs and HH subgraphs
Except the step of in, in described image processing unit, can keep or change by following mathematical expressions 12 with the detection
Strong edge, wavelet coefficient values corresponding to weak edge and noise.
(mathematical expression 12)
Here, wi,jRepresent the small echo of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Coefficient；w'i,jRepresent the wavelet systems of the modification of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Number；K, p represents variable, is adjustable value；σ represents the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs
Standard deviation.
Performing the improvement of contrast and going for noise for the LH subgraphs, HL subgraphs and HH subgraphs
Except the step of after, the steps can also be included：In described image processing unit, by the LL subgraphs, LH subgraphs
Picture, HL subgraphs and HH subgraphs inverse wavelet transform are the image of luminance components；In described image processing unit, based on by
The color notation conversion space and the luminance components extracted and the luminance components that are obtained by the inverse wavelet transform are to adjust
The color of input picture is stated, so as to output result image.
In the step of adjusting the color of input picture and output result image, it can be adjusted by following mathematical expressions 13
The color of the whole input picture.
(mathematical expression 13)
Here, Y represents the luminance components from the extraction of color notation conversion space portion；YeRepresent from the bright of inverse wavelet transform portion acquisition
Spend composition；[R, G, B] represents the RGB compositions of input picture；[R', G', B'] represents the RGB compositions of result images.
According to an embodiment of the invention, by carrying out wavelet transformation to input picture to make LL subgraph (that is, low bands
(Low-band) subgraph) the improvement improvement of contrast (contrast) is obtained in the first image enhancement portion, and make LH subgraphs
Picture, HL subgraphs and HH subgraphs (that is, high band (High-band) subgraph) obtain noise in the second image enhancement portion
Remove and the improvement of contrast is handled, so as to handle simultaneously and promptly the improvement of the contrast of input picture and make an uproar
The removal of sound.That is, divided the subgraph through wavelet transformation by low band and high band and improved pair by different modes
Than degree, so as to effectively improve the contrast of overall input picture suitable for frequency domain.In addition, the first image enhancement portion and
Two image enhancement portions can be performed in parallel image procossing, so as to handle simultaneously and promptly the contrast of input picture
Improvement and the removal of noise.
Brief description of the drawings
Fig. 1 is the module map for the composition for representing the image processing apparatus according to one embodiment of the invention.
Fig. 2 is that the input picture (Fig. 2 (a)) according to one embodiment of the invention and result images (Fig. 2 (b)) are entered
The figure that row compares.
Fig. 3 is the flow chart for illustrating the image processing method according to one embodiment of the invention.
Fig. 4 is illustrative for the module of computing environment of the explanation comprising the computing device for being suitable for exemplary embodiment
Figure.
Symbol description
100：Image processing apparatus
102：Color notation conversion space portion
104：Standardization Sector
106：Wavelet transformation portion
108：First image enhancement portion
110：Second image enhancement portion
112：Inverse wavelet transform portion
114：Color adjustment portion
Embodiment
Hereinafter, refer to the attached drawing and illustrate the present invention embodiment.Following detailed description is complete in order to contribute to
Method, apparatus and/or system described in foliation solution this specification and provide.But this is only an example, the present invention is simultaneously
It is not limited to this.
During embodiments of the invention are illustrated, if it is considered to being illustrated to known technology for the present invention
It is possible to cause unnecessary confusion to the purport of the present invention, then description is omitted.In addition, term described later allows for
Function in the present invention and the term defined, may because of user, intention or convention for transporting user etc. and it is different.Therefore, be with
It is defined based on the content of entire disclosure.The term used in detailed description is only used for notebook
The embodiment of invention, and it is not intended in any way to limit embodiments of the invention.Differently used as long as no clear and definite, then the statement of odd number
Include the implication of plural number.In this manual, the statement of " comprising " or " having " etc be used to referring to some characteristics, numeral,
Step, operation, key element and one part or the presence of combination, it should not be construed as excluding one or one in addition to described person
Other characteristics, numeral, step, operation, key element and one part above or existence or the property of may be present of combination.
In addition, embodiments of the invention may include the program for performing the method described by this specification on computers
And include the computer readable recording medium storing program for performing of described program.The computer readable recording medium storing program for performing can be by program command, sheet
Ground data file, local data structure etc. are included in a manner of alone or in combination.The medium can be for the present invention
And the medium for being specifically designed and forming, or can be the medium that can be generally used in computer software fields.Computer can
The example of read record medium includes the magnetizing mediums of hard disk, floppy disk and tape etc；CD-ROM, DVD etc optical recording media；
ROM, RAM, flash memory etc. are in order to store and configuration processor order and the hardware unit that is specially constructed.Not only wrapped in the example of described program
The machine language code made by means of compiler is included, but also can be held using interpreter etc. by computer
Capable higher-level language code.
Fig. 1 is the module map for the composition for representing the image processing apparatus according to one embodiment of the invention.Reference picture 1, figure
As processing unit 100 can include：Color notation conversion space portion 102, Standardization Sector 104, wavelet transformation portion 106, the first image change
Kind portion 108, the second image enhancement portion 110, inverse wavelet transform portion 112 and color adjustment portion 114.In an exemplary implementation
In example, image processing apparatus 100 can be used for the image quality for improving captured image under low-light (level) environment, but the present invention
Application is not limited thereto, and it may be obviously used for improving captured image under various environment in addition
Image quality.
The color space of the image of input can be transformed to YUV colors by color notation conversion space portion 102 by RGB color
Space.That is, color notation conversion space portion 102 can by input image pixels have R (red, Red), G (green, Green), B (it is blue,
Blue) color notation conversion space of composition is the color space with Y (brightness) and U, V (color signal) composition.In other words, face
The input picture of RGB color can be transformed to the color space with luminance components by color space transformation portion 102.
Color notation conversion space portion 102 can only extract luminance components from the input picture of RGB color.Color space
Transformation component 102 can extract Y (brightness) signal component value by following mathematical expression 1 from input picture.
[mathematical expression 1]
Y=0.299·R+0.587·G+0.144·B
Here, R, G, B represent red, green, the value of blue component in the pixel of input picture respectively.
Standardization Sector 104 can be standardized to brightness (Y) composition extracted from color notation conversion space portion 102.That is, from
Y (brightness) composition that color notation conversion space portion 102 extracts color table demonstration enclose it is narrower, therefore in order that color table demonstration enclose
Broaden, Y (brightness) composition can be standardized.In the exemplary embodiment, Standardization Sector 104 can be by following
Mathematical expression 2 and Y (brightness) composition is standardized.
[mathematical expression 2]
Here, YnorRepresent normalised Y (brightness) composition, YmaxRepresent the maximum of Y compositions, YminRepresent Y compositions
Minimum value.
Small echo (wavelet) transformation component 106 can carry out wavelet transformation to input picture.In the exemplary embodiment,
Wavelet transformation portion 106 can carry out wavelet transformation to the input picture of normalised Y (brightness) composition.Wavelet transformation portion 106
The wave filter group (filter bank) being made up of low frequency bandpass filter and high freguency bandpass filter can be included.Wavelet transformation
Portion 106 can respectively with vertical direction and horizontal direction application low frequency bandpass filter and high freguency bandpass filter, so as to
Generate 4 subgraphs.
That is, wavelet transformation portion 106 can generate 4 following subgraphs：By the image of low band and low band (with
Under, " LL subgraphs " can be referred to as), by the image of low band and high band (following, " LH subgraphs " can be referred to as), logical
Cross the image (following, " HL subgraphs " can be referred to as) of high band and low band, pass through the image of high band and high band
(following, " HH subgraphs " can be referred to as).
In the exemplary embodiment, wavelet transformation portion 106 can perform the wavelet transformation of three-level to input picture.Herein
In the case of, the size of the image after wavelet transformation will be changed into the 1/16 of original input image, therefore can reduce image procossing
Data volume and realize high speed processing.But the invention is not limited in this, wavelet transformation portion 106 obviously can also carry out various
Rank wavelet transformation.
LL subgraphs can be sent to the first image enhancement portion 108 by wavelet transformation portion 106, and by LH subgraphs, HL
Image and HH subgraphs are sent to the second image enhancement portion 110.Here, LL subgraphs, LH subgraphs, HL subgraphs and HH
Subgraph is the subgraph of final wavelet transformation rank (for example, three-level) respectively.
First image enhancement portion 108 can improve the contrast of LL subgraphs.I.e., in the exemplary embodiment, it will
Improve the contrast of input picture using the LL subgraphs of low-frequency band.Now, the first image enhancement portion 108 can be performed for limiting
Contrast limited adaptive histogram equalization (the Contrast of local contrast (contrast) gain (gain) processed
Limited Adaptive Histogram Equalization：CLAHE), to prevent the excessive improvement (over- of contrast
enhancement)。
Second image enhancement portion 110 can remove the noise of LH subgraphs, HL subgraphs and HH subgraphs (i.e.,
noise).I.e., in the exemplary embodiment, can utilize high frequency band LH subgraphs, HL subgraphs and HH subgraphs and
Remove the noise of input picture.Now, the second image enhancement portion 110 can be by LH subgraphs, HL subgraphs and HH
The edge line (that is, edge (edge)) of image is improved and is together improved it with contrast.Second image enhancement portion 110 from
Detect edge (edge) and noise region in LH subgraphs, HL subgraphs and HH subgraphs, and can be to the edge that detects
Detected noise is removed while improvement.
Specifically, noise is mainly appeared in high-frequency wavelet coefficient, and high-frequency wavelet coefficient can be divided into strong side
Edge (Strong Edge), weak edge (Weak Edge) and noise (Noise).Here, strong edge is in LH subgraphs, HL subgraphs
Higher wavelet coefficient values are respectively provided with picture and HH subgraphs.Weak edge is in LH subgraphs, HL subgraphs and HH subgraphs
In a certain subgraph in there are higher wavelet coefficient values, but will have relatively low wavelet coefficient in another subgraph
Value.Noise does not almost have directionality, therefore is respectively provided with relatively low wavelet systems in LH subgraphs, HL subgraphs and HH subgraphs
Numerical value.
Second image enhancement portion 110 can be by following mathematical expression 3 and in LH subgraphs, HL subgraphs and HH subgraphs
Strong edge, weak edge and noise are detected as in.
[mathematical expression 3]
mean(wI, j)≥kσ；Strong edge
mean(wI, j) ＜ k σ, max >=k σ；Weak edge
mean(wI, j) ＜ k σ, max ＜ k σ；Noise
Here, mean (wi, j) represents the office of the wavelet coefficient (w) of each LH subgraphs, HL subgraphs and HH subgraphs
Portion is averaged, and max represents the maximum of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs, and k is variable, is
Adjustable value, σ are the standard deviations of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs.Wi, j be
The wavelet coefficient of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs.
In addition, the second image enhancement portion 110 can be by following mathematical expression 4 and the standard deviation of computational mathematics formula 3
(σ)。
[mathematical expression 4]
Here, MAD (Median Absolute Deviation) represents each LH subgraphs, HL subgraphs and HH
The median absolute deviation of the wavelet coefficient of image.
Second image enhancement portion 110 can be to detecting from each LH subgraphs, HL subgraphs and HH subgraphs
Strong edge, weak edge and wavelet coefficient corresponding to noise modification.Specifically, to from each LH subgraphs, HL subgraphs with
And for the strong edge detected in HH subgraphs, due to by noise influenceed smaller, thus the second image enhancement portion 110
Corresponding wavelet coefficient values can be kept.To from the weak edge that each LH subgraphs, HL subgraphs and HH subgraphs detect
For, due to noise-sensitive, thus the second image enhancement portion 110 can change corresponding to wavelet coefficient values and improve contrast
Degree.In addition, for the noise detected from each LH subgraphs, HL subgraphs and HH subgraphs, the second image enhancement
Portion 110 can make corresponding wavelet coefficient values be set to 0 and remove it.
Second image enhancement portion 110 can by following mathematical expression 5 and change from each LH subgraphs, HL subgraphs with
And the wavelet coefficient corresponding to strong edge, weak edge and the noise detected in HH subgraphs.Accordingly, the second image enhancement portion
110 while noise is removed from each LH subgraphs, HL subgraphs and HH subgraphs, can also improve contrast.
[mathematical expression 5]
Here, w'i, j are the modifications of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs
Wavelet coefficient afterwards, and p is variable, it can be selected from 0~1 value.
I.e., in the exemplary embodiment, the contrast of the LL subgraphs of input picture is in the first image enhancement portion 108
Improvement processing is obtained, and the contrast of the LH subgraphs of input picture, HL subgraphs and HH subgraphs is in the second image enhancement
Improvement processing is obtained in portion 110, so as to handle simultaneously and promptly improvement and the noise of the contrast of input picture
Remove.
Inverse wavelet transform portion 112 receives LL subgraphs from the first image enhancement portion 108, and from the second image enhancement portion 110
Receive LH subgraphs, HL subgraphs and HH subgraphs.Inverse wavelet transform portion 112 is to LL subgraphs, LH subgraphs, HL subgraphs
And HH subgraphs carry out inverse wavelet transform.Inverse wavelet transform portion 112 can by LL subgraphs, LH subgraphs, HL subgraphs with
And the image that HH subgraphs inverse wavelet transform is Y (brightness) composition.
Color adjustment portion 114 is adjusted and output result image to the color of input picture.Color adjustment portion 114 can profit
Input figure is adjusted with the luminance components and the luminance components in inverse wavelet transform portion 112 that are extracted from color notation conversion space portion 102
The color of picture, and output result image.Hereby it is possible to it is naturally connected the boundary portion between the block of wavelet transformation and block
Point.Color adjustment portion 114 can adjust the color of input picture by following mathematical expression 6.
[mathematical expression 6]
Here, Y represents the luminance components extracted from spatial alternation portion 102, Ye represents what is obtained from inverse wavelet transform portion 112
Luminance components.[R', G', B'] represents the RGB compositions of the image (that is, result images) exported from color adjustment portion 114, [R, G,
B] represent input picture RGB compositions.
According to an embodiment of the invention, by carrying out wavelet transformation to input picture, improve in the first image enhancement portion 108
The contrast of LL subgraphs (that is, low band subgraph), and carried out in the second image enhancement portion 110 to LH subgraphs, HL subgraphs
The removal of the noise of picture and HH subgraphs (that is, high band subgraph) and the improvement processing of contrast, so as to simultaneously
And promptly handle the improvement of contrast and the removal of noise of input picture.
That is, divided the subgraph through wavelet transformation by low band and high band and improved contrast using different modes
Degree, effectively improves the contrast of whole input picture so as to be suitable for frequency domain.In addition, the first image enhancement portion 108
Image procossing can be performed in parallel with the second image enhancement portion 110, so as to handle simultaneously and promptly input picture
The improvement of contrast and the removal of noise.
Fig. 2 is that the input picture (Fig. 2 (a)) according to one embodiment of the invention and result images (Fig. 2 (b)) are entered
The figure that row compares.As shown in Figure 2, it can be seen that result images are improved compared to input picture, its overall image quality, from
And readability is improved.
Due to the image shot under the low-light (level) environment such as night or the weaker indoor environment of illumination occur it is more
Blind area, and the amount of the reflected light from subject reflection is less, and the reasons such as noise be present, readability will reduce.
However, by image processing apparatus 100 according to an embodiment of the invention, the image shot under low-light (level) environment can be improved
Image quality, so as to improve readability.Embodiments of the invention can apply to for installation security or security monitoring
Technology (for example, vehicle at night identification, number plate detection technology, invasion and theft detection technology etc.) based on solution.This
Outside, the figure captured by mobile terminal (for example, smart mobile phone, digital camera, tablet PC etc.) can also be applied to
Various fields such as the digital picture solution field of the image quality correction of picture etc.
Fig. 3 is the flow chart for illustrating the image processing method according to one embodiment of the invention.Side as shown in Figure 3
Method can perform by above-mentioned image processing apparatus 100.In illustrated flow chart, methods described is divided into multiple steps
It is rapid and recorded, but at least a portion step can be performed by exchange sequence, or with other steps with reference to and one
With performing, the step of being either omitted or being divided into sectionalization and perform, or increase it is (not shown) more than one the step of
And perform.
The color space of input picture is transformed to YUV face by reference picture 3, color notation conversion space portion 102 by RGB color
The colour space (S101).Now, color notation conversion space portion 102 can only extract brightness (Y) from the input picture of RGB color
Composition.
Afterwards, Standardization Sector 104 can be standardized to brightness (Y) composition extracted from color notation conversion space portion 102
(S103).That is, the color table demonstration of Y (brightness) composition extracted from color notation conversion space portion 102 enclose it is narrower, therefore to make face
Color table demonstration, which is enclosed, to be broadened, and Y (brightness) composition can be standardized.
Afterwards, wavelet transformation portion 106 can carry out wavelet transformation to the input picture of normalised Y (brightness) composition
(S105).Wavelet transformation portion 106 can be respectively with vertical direction and horizontal direction application low frequency bandpass filter and high frequency
Bandpass filter, so as to generate 4 subgraphs (that is, LL subgraphs, LH subgraphs, HL subgraphs and HH subgraphs).Small echo
LL subgraphs can be sent to the first image enhancement portion 108 by transformation component 106, and by LH subgraphs, HL subgraphs and HH
Image is sent to the second image enhancement portion 110.
Afterwards, the first image enhancement portion 108 is improved (S107) to the contrast of LL subgraphs.Image enhancement portion 108
Contrast limited adaptive histogram equalization (the Contrast for limiting local contrast gain (gain) can be performed
Limited Adaptive Histogram Equalization：CLAHE), to prevent the excessive improvement (over- of contrast
enhancement)。
In addition, strong edge detects from LH subgraphs, HL subgraphs and HH subgraphs in the second image enhancement portion 110
(Strong Edge), weak edge (Weak Edge) and noise (Noise) (S109).Second image enhancement portion 110 can lead to
Cross above-mentioned mathematical expression 3 and detect strong edge, weak edge and noise.
Afterwards, the second image enhancement portion 110 will detect from each LH subgraphs, HL subgraphs and HH subgraphs
Wavelet coefficient corresponding to strong edge, weak edge and noise is modified, to perform the removal of the improvement at edge and noise
(S111).Second image enhancement portion 110 wavelet coefficient is changed by above-mentioned mathematical expression 5.For strong edge, the second image
Improvement portion 110 can keep wavelet coefficient values；For weak edge, the second image enhancement portion 110 can change wavelet coefficient values
To improve contrast；For noise, wavelet coefficient values can be set to 0 and removed it by the second image enhancement portion 110.
Here, at the image procossing (S107 steps) in the first image enhancement portion 108 and the image in the second image enhancement portion 110
Reason (S109 steps, S111 steps) can be performed in parallel.
Afterwards, inverse wavelet transform portion 112 carries out inverse small to LL subgraphs, LH subgraphs, HL subgraphs and HH subgraphs
Wave conversion (S113).Inverse wavelet transform portion 112 can be by LL subgraphs, LH subgraphs, HL subgraphs and HH subgraphs against small
Wave conversion is the image of Y (brightness) composition.
Afterwards, color adjustment portion 114 is adjusted and output result image (S115) to the color of input picture.Color is adjusted
Whole 114 using from color notation conversion space portion 102 extract luminance components and inverse wavelet transform portion 112 luminance components and
Adjust the color of input picture, and output result image.Color adjustment portion 114 can be defeated to adjust by above-mentioned mathematical expression 6
Enter the color and output result image of image.
Fig. 4 is illustrative for the mould of computing environment 10 of the explanation comprising the computing device for being suitable for exemplary embodiment
Block figure.In the illustrated embodiment, each component can also have in addition to content described below different function and
Ability, and extra component can also be included in addition to content described below.
The computing environment 10 of diagram includes computing device 12.In one embodiment, computing device 12 can be used to carry out
The device (for example, image processing apparatus 100) of image procossing.
Computing device 12 includes at least one processor 14, computer-readable recording medium 16 and communication bus (bus)
18.Processor 14 can be such that computing device 12 is operated according to exemplary embodiment mentioned above.For example, processor 14 can
Perform the more than one program for being stored in computer-readable recording medium 16.Program more than one can include one
More than computer executable instruction, the executable instruction of the computer can be configured to perform by processor 14
In the case of, computing device 12 is performed the operation according to exemplary embodiment.
Computer-readable recording medium 16 with can store the executable instruction of computer to program code, routine data with
And/or the mode of the information of person other suitable forms is formed.The program 20 being stored in computer-readable recording medium 16 is wrapped
Containing the instruction set that can be performed by processor 14.In one embodiment, computer-readable recording medium 16 can be that memory is (random
Access the suitable combining form of the volatile memory, nonvolatile memory or these memories such as memory), one with
On disk storage equipment, optical disc memory apparatus, flash memory device, in addition can be accessed by computing device 12 and can
Store the storage medium of the other forms of desired information or these suitable combining form.
Communication bus 18 be used for including processor 14, computer-readable recording medium 16 by computing device 12 other
Various component is connected with each other.
In addition, computing device 12 can also include one of offer for the interface of more than one input/output unit 24
Input/output interface 22 and more than one network communication interface 26 above.Input/output interface 22 and network service connect
Mouth 26 is connected to communication bus 18.Input/output unit 24 can be connected to computing device 12 by input/output interface 22
Other assemblies.Exemplary input/output unit 24 can include：Such as pointing device (mouse or Trackpad (track
Pad) etc.), keyboard, touch input device (touch pad either touch-screen etc.), voice or acoustic input dephonoprojectoscope, various species
Sensor device and/or filming apparatus etc. input unit；And/or such as display device, printing machine, loudspeaker
And/or the output device of network interface card (network card) etc..Exemplary input/output unit 24, which can be used as, is used for structure
The inside of computing device 12 is included in into a component of computing device 12, can also be as the independence for being different from computing device 12
Device and be connected to computing device 102.
More than, it has been detailed that representative embodiment of the invention, but there is base in the technical field belonging to the present invention
The personnel of this knowledge presumably understand can be subject to various deformation in the limit for do not depart from the scope of the present invention to above-described embodiment.
Therefore, interest field of the invention should not be limited to described embodiment and determine, but should be remembered according to claims
Scope and its equivalents thereto of load and determine.
Claims (27)
1. a kind of image processing apparatus, including：
Color notation conversion space portion, luminance components are extracted from the input picture by converting the color space of input picture；
Wavelet transformation portion, wavelet transformation is carried out to the input picture of the luminance components and generates LL subgraphs, LH subgraphs, HL
Subgraph and HH subgraphs；
First image enhancement portion, the LL subgraphs are received from the wavelet transformation portion, and improve the contrast of the LL subgraphs
Degree；And
Second image enhancement portion, LH subgraphs, HL subgraphs and the HH subgraphs are received from the wavelet transformation portion, and held
The improvement of contrast and the removal of noise of the hand-manipulating of needle to the LH subgraphs, HL subgraphs and HH subgraphs.
2. image processing apparatus as claimed in claim 1, wherein,
The improvement of the contrast of the LL subgraphs and changing for the contrast of the LH subgraphs, HL subgraphs and HH subgraphs
Kind and noise removal is performed in parallel in described first image improvement portion and the second image enhancement portion.
3. image processing apparatus as claimed in claim 1, wherein,
Described image processing unit also includes：Standardization Sector, to by the brightness that the color notation conversion space portion extracts into
Divide and be standardized and the input picture of the normalised luminance components is delivered to the wavelet transformation portion.
4. image processing apparatus as claimed in claim 3, wherein,
The Standardization Sector is standardized by following mathematical expressions 1 to the luminance components extracted,
Mathematical expression 1
<mrow>
<msub>
<mi>y</mi>
<mrow>
<mi>n</mi>
<mi>o</mi>
<mi>r</mi>
</mrow>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mi>Y</mi>
<mo>-</mo>
<msub>
<mi>Y</mi>
<mrow>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
</mrow>
</msub>
</mrow>
<mrow>
<msub>
<mi>Y</mi>
<mi>max</mi>
</msub>
<mo>-</mo>
<msub>
<mi>Y</mi>
<mi>min</mi>
</msub>
</mrow>
</mfrac>
<mo>&times;</mo>
<mn>255</mn>
</mrow>
Here, YnorRepresent normalised luminance components；YmaxRepresent the maximum of luminance components extracted；YminExpression carries
The minimum value for the luminance components got.
5. image processing apparatus as claimed in claim 1, wherein,
Examined in the LH subgraphs, HL subgraphs and HH subgraphs according to wavelet coefficient values in the second image enhancement portion
Strong edge, weak edge and noise are surveyed, and keeps or changes corresponding to the small of strong edge, weak edge and the noise detected
Wave system numerical value, so as to perform the improvement of the contrast for the LH subgraphs, HL subgraphs and HH subgraphs and noise
Removal.
6. image processing apparatus as claimed in claim 5, wherein,
The strong edge, weak edge and noise detect by following mathematical expressions 2 in the second image enhancement portion,
Mathematical expression 2
mean(wI, j)≥kσ；Strong edge
mean(wI, j) ＜ k σ, max >=k σ；Weak edge
mean(wI, j) ＜ k σ, max ＜ k σ；Noise
Here, wi,jRepresent the wavelet coefficient of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs；
mean(wi,j) represent each LH subgraphs, HL subgraphs and HH subgraphs wavelet coefficient (w) local average；Max is represented
The maximum of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs；K represents variable, is adjustable value；σ
Represent the standard deviation of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs.
7. image processing apparatus as claimed in claim 6, wherein,
The second image enhancement portion calculates the standard deviation by following mathematical expressions 3,
Mathematical expression 3
<mrow>
<mi>&sigma;</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mi>M</mi>
<mi>A</mi>
<mi>D</mi>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>|</mo>
<mo>)</mo>
</mrow>
</mrow>
<mn>0.6745</mn>
</mfrac>
</mrow>
Here, MAD represents the median absolute deviation of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs.
8. image processing apparatus as claimed in claim 5, wherein,
The second image enhancement portion keeps or changed and the strong edge of the detection, weak side by following mathematical expressions 4
Wavelet coefficient values corresponding to edge and noise：
Mathematical expression 4
Here, wi,jRepresent the wavelet coefficient of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs；
w'i,jRepresent the modified wavelet coefficient of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs；
K, p represents variable, is adjustable value；σ represents the mark of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs
Quasi- deviation.
9. image processing apparatus as claimed in claim 1, wherein,
Described image processing unit also includes：Inverse wavelet transform portion, by the LL subgraphs, LH subgraphs, HL subgraphs and
HH subgraphs inverse wavelet transform is the image of luminance components.
10. image processing apparatus as claimed in claim 9, wherein,
Described image processing unit is become based on the luminance components extracted from the color notation conversion space portion and from the inverse small echo
The luminance components for changing portion's acquisition adjust the color of the input picture, so as to output result image.
11. image processing apparatus as claimed in claim 10, wherein,
The color adjustment portion adjusts the color of the input picture by following mathematical expressions 5,
Mathematical expression 5
<mrow>
<mfenced open = "[" close = "]">
<mtable>
<mtr>
<mtd>
<msup>
<mi>R</mi>
<mo>&prime;</mo>
</msup>
</mtd>
</mtr>
<mtr>
<mtd>
<msup>
<mi>G</mi>
<mo>&prime;</mo>
</msup>
</mtd>
</mtr>
<mtr>
<mtd>
<msup>
<mi>B</mi>
<mo>&prime;</mo>
</msup>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>=</mo>
<mfenced open = "[" close = "]">
<mtable>
<mtr>
<mtd>
<mfrac>
<msub>
<mi>Y</mi>
<mi>e</mi>
</msub>
<mi>Y</mi>
</mfrac>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
</mtr>
<mtr>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mfrac>
<msub>
<mi>Y</mi>
<mi>e</mi>
</msub>
<mi>Y</mi>
</mfrac>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
</mtr>
<mtr>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mfrac>
<msub>
<mi>Y</mi>
<mi>e</mi>
</msub>
<mi>Y</mi>
</mfrac>
</mtd>
</mtr>
</mtable>
</mfenced>
<mfenced open = "[" close = "]">
<mtable>
<mtr>
<mtd>
<mi>R</mi>
</mtd>
</mtr>
<mtr>
<mtd>
<mi>G</mi>
</mtd>
</mtr>
<mtr>
<mtd>
<mi>B</mi>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
Here, Y represents the luminance components from the extraction of color notation conversion space portion；YeRepresent from inverse wavelet transform portion obtain brightness into
Point；[R, G, B] represents the RGB compositions of input picture；[R', G', B'] represents the RGB compositions of result images.
12. a kind of computing device, including：
More than one processor；
Memory；
More than one program,
Program storage more than one performs in the memory, and by one processor above,
Program more than one includes：For to input picture carry out wavelet transformation and generate LL subgraphs, LH subgraphs,
The instruction of HL subgraphs and HH subgraphs；
For the instruction for the contrast for improving the LL subgraphs；
For performing the improvement to the contrast of the LH subgraphs, HL subgraphs and HH subgraphs and the removal of noise
Instruction.
13. computing device as claimed in claim 12, wherein,
The improvement of the contrast of the LL subgraphs and changing for the contrast of the LH subgraphs, HL subgraphs and HH subgraphs
Kind and noise removal is performed in parallel in the computing device.
14. computing device as claimed in claim 12, wherein,
For the contrast that performs the LH subgraphs, HL subgraphs and HH subgraphs improvement and noise removal finger
Order includes following instruction：
For detecting strong edge, weak side according to wavelet coefficient values in the LH subgraphs, HL subgraphs and HH subgraphs
The instruction of edge and noise；And
For being held by keeping or changing wavelet coefficient values corresponding with the strong edge of the detection, weak edge and noise
The improvement of contrast and the removal of noise of the hand-manipulating of needle to the LH subgraphs, HL subgraphs and HH subgraphs.
15. computing device as claimed in claim 14, wherein,
Program more than one includes：For detecting the strong edge, weak edge by following mathematical expressions 6 and making an uproar
The instruction of sound,
Mathematical expression 6
mean(wI, j)≥kσ；Strong edge
mean(wI, j) ＜ k σ, max >=k σ；Weak edge
mean(wI, j) ＜ k σ, max ＜ k σ；Noise
Here, wi,jRepresent the wavelet coefficient of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs；
mean(wi,j) represent each LH subgraphs, HL subgraphs and HH subgraphs wavelet coefficient (w) local average；Max is represented
The maximum of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs；K represents variable, is adjustable value；σ
Represent the standard deviation of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs.
16. computing device as claimed in claim 15, wherein,
Program more than one includes being used to calculate the instruction of the standard deviation by following mathematical expressions 7,
Mathematical expression 7
<mrow>
<mi>&sigma;</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mi>M</mi>
<mi>A</mi>
<mi>D</mi>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>|</mo>
<mo>)</mo>
</mrow>
</mrow>
<mn>0.6745</mn>
</mfrac>
</mrow>
Here, MAD represents the median absolute deviation of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs.
17. computing device as claimed in claim 14, wherein,
Program more than one includes being used to keep or change the strong side with the detection by following mathematical expressions 8
The instruction of edge, weak edge and wavelet coefficient values corresponding to noise,
Mathematical expression 8
Here, wi,jRepresent the wavelet coefficient of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs；
w'i,jRepresent the wavelet coefficient of the modification of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs；k、
P represents variable, is adjustable value；σ represents the standard of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs
Deviation.
18. a kind of image processing method, including the steps：
In image processing apparatus, by convert the color space of input picture and from the input picture extract brightness into
Point；
In described image processing unit, wavelet transformation is carried out to the input pictures of the luminance components and generate LL subgraphs,
LH subgraphs, HL subgraphs and HH subgraphs；
In described image processing unit, improve the contrast of the LL subgraphs；And
In described image processing unit, execution is for the contrast of the LH subgraphs, HL subgraphs and HH subgraphs
Improvement and the removal of noise.
19. image processing method as claimed in claim 18, wherein,
In described image processing unit, the step of being performed in parallel improving the contrast of the LL subgraphs and perform and be directed to institute
State the contrast of LH subgraphs, HL subgraphs and HH subgraphs improvement and noise removal the step of.
20. image processing method as claimed in claim 19, wherein,
After performing the step of luminance components are extracted from the input picture, in addition to the steps：
In described image processing unit, the luminance components extracted by the color notation conversion space portion are standardized.
21. image processing method as claimed in claim 20, wherein,
In the step of standardization, in described image processing unit, by following mathematical expressions 9 and to the extraction
Luminance components are standardized,
Mathematical expression 9
<mrow>
<msub>
<mi>Y</mi>
<mrow>
<mi>n</mi>
<mi>o</mi>
<mi>r</mi>
</mrow>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mi>Y</mi>
<mo>-</mo>
<msub>
<mi>Y</mi>
<mi>min</mi>
</msub>
</mrow>
<mrow>
<msub>
<mi>Y</mi>
<mi>max</mi>
</msub>
<mo>-</mo>
<msub>
<mi>Y</mi>
<mrow>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
</mrow>
</msub>
</mrow>
</mfrac>
<mo>&times;</mo>
<mn>255</mn>
</mrow>
Here, YnorRepresent normalised luminance components；YmaxRepresent the maximum of luminance components extracted；YminExpression carries
The minimum value for the luminance components got.
22. image processing method as claimed in claim 18, wherein,
Perform the step for the improvement of the contrast of the LH subgraphs, HL subgraphs and HH subgraphs and the removal of noise
Suddenly the steps is included：
In described image processing unit, according to wavelet coefficient values in the LH subgraphs, HL subgraphs and HH subgraphs
And detect strong edge, weak edge and noise；
In described image processing unit, keep or modification is corresponding to the small of strong edge, weak edge and the noise detected
Wave system numerical value, so as to perform the improvement of the contrast for the LH subgraphs, HL subgraphs and HH subgraphs and noise
Removal.
23. image processing method as claimed in claim 22, wherein,
In the step of detecting the strong edge, weak edge and noise, the strong side is detected by following mathematical expressions 10
Edge, weak edge and noise,
Mathematical expression 10
mean(wI, j)≥kσ；Strong edge
mean(wI, j) ＜ k σ, max >=k σ；Weak edge
mean(wI, j) ＜ k σ, max ＜ k σ；Noise
Here, wi,jRepresent the wavelet coefficient of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs；
mean(wi,j) represent each LH subgraphs, HL subgraphs and HH subgraphs wavelet coefficient (w) local average；Max is represented
The maximum of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs；K represents variable, is adjustable value；σ
Represent the standard deviation of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs.
24. image processing method as claimed in claim 23, wherein,
In the step of detecting the strong edge, weak edge and noise, the standard is calculated by following mathematical expressions 11
Deviation,
Mathematical expression 11
<mrow>
<mi>&sigma;</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mi>M</mi>
<mi>A</mi>
<mi>D</mi>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>|</mo>
<mo>)</mo>
</mrow>
</mrow>
<mn>0.6745</mn>
</mfrac>
</mrow>
Here, MAD represents the median absolute deviation of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs.
25. image processing method as claimed in claim 22, wherein,
In the improvement and the removal of noise for performing the contrast for being directed to the LH subgraphs, HL subgraphs and HH subgraphs
In step,
In described image processing unit, by following mathematical expressions 12 and keep or change with the strong edge of the detection,
Wavelet coefficient values corresponding to weak edge and noise,
Mathematical expression 12
Here, wi,jRepresent the wavelet coefficient of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs；
w'i,jRepresent the wavelet coefficient of the modification of (i, j) coordinate pixel in each LH subgraphs, HL subgraphs and HH subgraphs；k、
P represents variable, is adjustable value；σ represents the standard of the wavelet coefficient of each LH subgraphs, HL subgraphs and HH subgraphs
Deviation.
26. image processing method as claimed in claim 18, wherein,
In the improvement and the removal of noise for performing the contrast for being directed to the LH subgraphs, HL subgraphs and HH subgraphs
After step, in addition to the steps：
In described image processing unit, the LL subgraphs, LH subgraphs, HL subgraphs and HH subgraphs are become against small echo
It is changed to the image of luminance components；
In described image processing unit, based on the luminance components extracted by the color notation conversion space and by described inverse small
Wave conversion and the luminance components that obtain adjust the color of the input picture, so as to output result image.
27. image processing method as claimed in claim 26, wherein,
In the step of adjusting the color of the input picture and output result image, by following mathematical expressions 13 to adjust
The color of input picture is stated,
Mathematical expression 13
<mrow>
<mfenced open = "[" close = "]">
<mtable>
<mtr>
<mtd>
<msup>
<mi>R</mi>
<mo>&prime;</mo>
</msup>
</mtd>
</mtr>
<mtr>
<mtd>
<msup>
<mi>G</mi>
<mo>&prime;</mo>
</msup>
</mtd>
</mtr>
<mtr>
<mtd>
<msup>
<mi>B</mi>
<mo>&prime;</mo>
</msup>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>=</mo>
<mfenced open = "[" close = "]">
<mtable>
<mtr>
<mtd>
<mfrac>
<msub>
<mi>Y</mi>
<mi>e</mi>
</msub>
<mi>Y</mi>
</mfrac>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
</mtr>
<mtr>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mfrac>
<msub>
<mi>Y</mi>
<mi>e</mi>
</msub>
<mi>Y</mi>
</mfrac>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
</mtr>
<mtr>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mfrac>
<msub>
<mi>Y</mi>
<mi>e</mi>
</msub>
<mi>Y</mi>
</mfrac>
</mtd>
</mtr>
</mtable>
</mfenced>
<mfenced open = "[" close = "]">
<mtable>
<mtr>
<mtd>
<mi>R</mi>
</mtd>
</mtr>
<mtr>
<mtd>
<mi>G</mi>
</mtd>
</mtr>
<mtr>
<mtd>
<mi>B</mi>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
Here, Y represents the luminance components from the extraction of color notation conversion space portion；YeRepresent from inverse wavelet transform portion obtain brightness into
Point；[R, G, B] represents the RGB compositions of input picture；[R', G', B'] represents the RGB compositions of result images.
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| CN201610333433.8A CN107403412A (en) | 2016-05-19 | 2016-05-19 | Image processing method and apparatus for carrying out the method |
| KR1020160083511A KR20170131812A (en) | 2016-05-19 | 2016-07-01 | Method for processing image and apparatus for executing the method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101958194B1 (en) * | 2017-11-30 | 2019-03-15 | 인천대학교 산학협력단 | Apparatus and method for contrast enhancement in transform domain |
| CN111756954A (en) * | 2020-07-14 | 2020-10-09 | 北京字节跳动网络技术有限公司 | Image processing method, image processing device, electronic equipment and computer readable medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1542693A (en) * | 2003-04-15 | 2004-11-03 | ������������ʽ���� | Image processing method, image processing apparatus and image processing program |
| CN101493939A (en) * | 2009-02-27 | 2009-07-29 | 西北工业大学 | Method for detecting cooked image based on small wave domain homomorphic filtering |
| CN105243641A (en) * | 2015-08-18 | 2016-01-13 | 西安电子科技大学 | Low illumination image enhancement method based on dual-tree complex wavelet transform |
-
2016
- 2016-05-19 CN CN201610333433.8A patent/CN107403412A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1542693A (en) * | 2003-04-15 | 2004-11-03 | ������������ʽ���� | Image processing method, image processing apparatus and image processing program |
| CN101493939A (en) * | 2009-02-27 | 2009-07-29 | 西北工业大学 | Method for detecting cooked image based on small wave domain homomorphic filtering |
| CN105243641A (en) * | 2015-08-18 | 2016-01-13 | 西安电子科技大学 | Low illumination image enhancement method based on dual-tree complex wavelet transform |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101958194B1 (en) * | 2017-11-30 | 2019-03-15 | 인천대학교 산학협력단 | Apparatus and method for contrast enhancement in transform domain |
| CN111756954A (en) * | 2020-07-14 | 2020-10-09 | 北京字节跳动网络技术有限公司 | Image processing method, image processing device, electronic equipment and computer readable medium |
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| KR20170131812A (en) | 2017-11-30 |
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