CN106530252B

CN106530252B - Image processing method and device

Info

Publication number: CN106530252B
Application number: CN201610980360.1A
Authority: CN
Inventors: 孙恒
Original assignee: Beijing Xiaomi Mobile Software Co Ltd
Current assignee: Beijing Xiaomi Mobile Software Co Ltd
Priority date: 2016-11-08
Filing date: 2016-11-08
Publication date: 2019-07-16
Anticipated expiration: 2036-11-08
Also published as: CN106530252A

Abstract

The disclosure is directed to image processing method and devices.This method comprises: target image to be processed is carried out Fuzzy Processing, with each pixel of the target image after being obscured on three channels of color model corresponding first component；To each pixel, corresponding first component carries out brightness adjustment in color model triple channel, obtains each pixel corresponding second component in color model triple channel；To each pixel, corresponding second component carries out saturation degree compensation in color model triple channel；To each pixel after saturation degree compensation, corresponding component carries out brightness and reduces adjustment in color model triple channel.The technical solution, to image carry out Fuzzy Processing when, can to the image after Fuzzy Processing carry out saturation degree compensation and suitably reduction Fuzzy Processing after image to specific luminance.

Description

Image processing method and device

Technical field

This disclosure relates to image technique field more particularly to image processing method and device.

Background technique

Currently, more excellent in order to make to shoot the image quality come, user can all use substantially various image processing softwares into Row mill skin processing, and mill skin in the related technology operate in the common mill skin algorithm image data that makes that treated in each picture The difference of vegetarian refreshments and surrounding pixel point reduces, specific manifestation are as follows: if the pixel value of current pixel point adding lower than adjacent pixels point When weight average pixel value, the pixel value of current pixel point increases to approach adjacent pixels point；If the pixel value of current pixel point is big When the weighted average pixel value of adjacent pixels point value, the pixel value of current pixel point reduces to approach adjacent pixels point, thus The mill skin operation of image is completed eventually by the pixel value of the pixel value substitution current pixel point of the pixel after using averagely, And for original image, the color of image after mill skin operation can become for obtained mill skin image after the operation of above-mentioned mill skin It is light, and grind the brightness of image after skin operation and improve very much, it will cause the feeling of whiting, so as to cause the image fault after mill skin, The visual experience of user is greatly reduced, so that the image after mill skin can allow user to generate false feeling.

Summary of the invention

The embodiment of the present disclosure provides image processing method and device.The technical solution is as follows:

According to the first aspect of the embodiments of the present disclosure, a kind of image processing method is provided, comprising:

Target image to be processed is subjected to Fuzzy Processing, with each pixel of the target image after being obscured Corresponding first component on three channels of color model；

To each pixel, corresponding first component carries out brightness adjustment in the color model triple channel, obtains Each pixel corresponding second component in the color model triple channel；

To each pixel, corresponding second component carries out saturation degree compensation in the color model triple channel；

To each pixel after saturation degree compensation, corresponding component is carried out in the color model triple channel Brightness reduces adjustment.

In one embodiment, described that target image to be processed is subjected to Fuzzy Processing, described in after being obscured Each pixel of target image corresponding first component on three channels of color model, comprising:

The target image is subjected to Fuzzy Processing, each pixel of the target image after being obscured is default First pixel value components in channel, wherein first pixel value components are used to characterize the every of the target image after obscuring Brightness of a pixel on the default channel；

Existed according to first pixel value components of each pixel and each pixel of the Fuzzy Processing foregoing description Original pixel value component on the default channel obtains second pixel value of each pixel on the default channel Component, wherein second pixel value components are for characterizing by first pixel value components and each pixel in institute State the brightness of each pixel that the original pixel value component on default channel obtains on the default channel；

According to second pixel value components of each pixel, each pixel is obtained in color model Corresponding first component on three channels.

In one embodiment, described that the target image is subjected to Fuzzy Processing, the target figure after being obscured First pixel value components of each pixel of picture in default channel, comprising:

According to original pixel value component of each pixel on the default channel and each pixel institute Each of reference zone original pixel value component of other pixels on the default channel, obtain each picture First pixel value components of vegetarian refreshments, wherein the default channel includes: the G in the color model (RGB) triple channel logical Road, alternatively, the channel Y in color space (YUV) triple channel.

In one embodiment, the original pixel value component according to each pixel on the default channel With each of reference zone where each pixel original pixel value of other pixels on the default channel Component obtains first pixel value components of each pixel, comprising:

According to the first default Fuzzy Processing function, to original pixel value of each pixel on the default channel Component carries out Fuzzy Processing, obtains first pixel value components of each pixel on the default channel, wherein The first default Fuzzy Processing function includes:

Wherein, the reference zone is the square area put centered on each pixel, the square region The side length in domain be comprising the occupied length of+1 pixel of 2 γ including each pixel,

Y indicates preset pixel value threshold value,

x₁Indicate the original pixel value component of each pixel on the default channel,

x_iIndicate each original pixel value of other pixels on the default channel point in square area Amount,

X indicates first pixel value components of each pixel on the default channel.

In one embodiment, first pixel value components and Fuzzy Processing according to each pixel it Original pixel value component of the preceding each pixel on the default channel obtains each pixel described default The second pixel value components on channel, comprising:

According to the first preset formula in the second default Fuzzy Processing function, each pixel of the Fuzzy Processing foregoing description is obtained Put described first in the original pixel value component and each pixel on the default channel on the default channel The initial pixel of pixel value components is poor, wherein the second default Fuzzy Processing function includes: first preset formula and Two preset formulas；

It is poor to determine whether the initial pixel difference is less than presetted pixel；

When the initial pixel difference is less than the presetted pixel difference, the first public affairs in second preset formula are executed Formula；

When the initial pixel difference is greater than or equal to the presetted pixel difference, the in second preset formula is executed Two formula；

The second preset formula N is being executed after, obtained final pixel difference is substituted into first preset formula In, obtain second pixel value components of each pixel on the default channel, wherein N is just more than or equal to 1 Integer,

First preset formula:

HighPass=x₁-x

First formula in second preset formula:

HighPass=2.0*highPass*highPass

Second formula in second preset formula:

HighPass=1-2.0* (1-highPass) * (1-highPass)

Wherein, x₁Indicate the original pixel value component of each pixel on the default channel, HighPass indicates that the initial pixel difference or the final pixel are poor,

When obtaining the initial pixel difference highPass according to first preset formula for the first time, the x indicates described every First pixel value components of a pixel,

Execute the second preset formula N all over, obtained final pixel difference highPass substitution described first preset After formula, the x indicates second pixel value components of each pixel.

In one embodiment, second pixel value components according to each pixel obtain described every A pixel corresponding first component in color model triple channel, comprising:

By second pixel value components of each pixel successively with each pixel in target triple channel On each original pixel value component be weighted summation, obtain first mesh of each pixel in the target triple channel Mark pixel value, wherein the target triple channel includes: the color model triple channel or color space triple channel；

According to the first object pixel value of each pixel, each pixel is obtained in the color mould Corresponding first component in type triple channel；

It is described that each pixel, corresponding first component carries out brightness adjustment in the color model triple channel, Include:

According to preset image gamma value, to each pixel corresponding first in the color model triple channel Component carries out power operation；

Using each pixel obtained after power operation corresponding second point in the color model triple channel Measure corresponding first component in the color model triple channel of each pixel before replacing power operation.

In one embodiment, it is described to each pixel corresponding second point in the color model triple channel Amount carries out saturation degree compensation, comprising:

According to each pixel obtained after power operation corresponding second point in the color model triple channel Amount, determines the second target pixel value of each pixel；

By each original pixel value of second target pixel value of each pixel and each pixel point Original pixel value composed by measuring is weighted summation, obtains the third target pixel value of each pixel；

According to the third target pixel value of each pixel, each pixel is obtained in the color mould Corresponding third component in type triple channel；

Using default saturation degree matrix, to each pixel, the corresponding third in the color model triple channel is divided Amount carries out saturation degree compensation, obtains each pixel corresponding 4th component in the color model triple channel.

In one embodiment, each pixel after the compensation to saturation degree is in the color model threeway Corresponding component, which carries out brightness, on road reduces adjustment, comprising:

According to the inverse of the preset image gamma value, to each pixel in the color model triple channel Corresponding 4th component carries out power operation.

In one embodiment, the method also includes:

Before carrying out Fuzzy Processing to the target image, by the pixel value of each pixel in the target image It is normalized.

According to the second aspect of an embodiment of the present disclosure, a kind of image processing apparatus is provided, comprising:

First processing module, for target image to be processed to be carried out Fuzzy Processing, with the mesh after being obscured Each pixel of logo image corresponding first component on three channels of color model；

The first adjustment module, for each pixel in the color model triple channel corresponding first component Brightness adjustment is carried out, each pixel corresponding second component in the color model triple channel is obtained；

Compensating module, for corresponding second component to carry out in the color model triple channel to each pixel Saturation degree compensation；

Second adjustment module, for each pixel after compensating saturation degree in the color model triple channel Upper corresponding component, which carries out brightness, reduces adjustment.

In one embodiment, the first processing module includes:

Submodule is handled, for the target image to be carried out Fuzzy Processing, the target image after being obscured First pixel value components of each pixel in default channel, wherein first pixel value components for characterize it is fuzzy after Brightness of each pixel of the target image on the default channel；

First acquisition submodule, for according to first pixel value components and Fuzzy Processing of each pixel it Original pixel value component of the preceding each pixel on the default channel obtains each pixel described default The second pixel value components on channel, wherein second pixel value components for characterizing by first pixel value components and Each pixel that original pixel value component of each pixel on the default channel obtains is described default Brightness on channel；

Second acquisition submodule obtains described every for second pixel value components according to each pixel A pixel corresponding first component on three channels of color model.

In one embodiment, the processing submodule includes:

First acquisition unit, for according to original pixel value component of each pixel on the default channel and Original pixel value of other pixels of each of reference zone where each pixel on the default channel point Amount, obtains first pixel value components of each pixel, wherein the default channel includes: the color model (RGB) channel G in triple channel, alternatively, the channel Y in color space (YUV) triple channel.

In one embodiment, the first acquisition unit includes:

Subelement is handled, for leading in described preset to each pixel according to the first default Fuzzy Processing function Original pixel value component on road carries out Fuzzy Processing, obtains described first of each pixel on the default channel Pixel value components, wherein the first default Fuzzy Processing function includes:

Y indicates preset pixel value threshold value,

X indicates first pixel value components of each pixel on the default channel.

In one embodiment, first acquisition submodule includes:

Second acquisition unit, for obtaining fuzzy place according to the first preset formula in the second default Fuzzy Processing function Original pixel value component and each pixel of each pixel of the foregoing description on the default channel are managed described pre- If the initial pixel of first pixel value components on channel is poor, wherein the second default Fuzzy Processing function includes: institute State the first preset formula and the second preset formula；

Determination unit, for determining it is poor whether the initial pixel difference is less than presetted pixel；

First execution unit, for it is pre- to execute described second when the initial pixel difference is less than the presetted pixel difference If the first formula in formula；

Second execution unit is used for when the initial pixel difference is greater than or equal to the presetted pixel difference, described in execution The second formula in second preset formula；

Third acquiring unit substitutes into obtained final pixel difference for executing the second preset formula N after In first preset formula, second pixel value components of each pixel on the default channel are obtained, wherein N For the positive integer more than or equal to 1,

First preset formula:

HighPass=x₁-x

First formula in second preset formula:

HighPass=2.0*highPass*highPass

Second formula in second preset formula:

HighPass=1-2.0* (1-highPass) * (1-highPass)

In one embodiment, second acquisition submodule includes:

Summation unit, for by second pixel value components of each pixel successively with each pixel Each original pixel value component in target triple channel is weighted summation, obtains each pixel in the target threeway First object pixel value on road, wherein the target triple channel includes: the color model triple channel or color space Triple channel；

4th acquiring unit obtains described each for the first object pixel value according to each pixel Pixel corresponding first component in the color model triple channel；

The first adjustment module includes:

First operation submodule is used for according to preset image gamma value, to each pixel in the color mould Corresponding first component carries out power operation in type triple channel；

Submodule is replaced, each pixel for obtaining later using power operation is in the color model triple channel Each pixel before upper corresponding second component replacement power operation is corresponding the in the color model triple channel One component.

In one embodiment, the compensating module includes:

Determine submodule, each pixel for obtaining later according to power operation is in the color model triple channel Upper corresponding second component, determines the second target pixel value of each pixel；

Third acquisition submodule, for by second target pixel value of each pixel and each pixel Original pixel value composed by each original pixel value component of point is weighted summation, obtains the third mesh of each pixel Mark pixel value；

4th acquisition submodule obtains described every for the third target pixel value according to each pixel A pixel corresponding third component in the color model triple channel；

Submodule is compensated, for using default saturation degree matrix to each pixel in the color model triple channel Upper corresponding third component carries out saturation degree compensation, and it is corresponding in the color model triple channel to obtain each pixel 4th component.

In one embodiment, the second adjustment module includes:

Second operation submodule exists to each pixel for the inverse according to the preset image gamma value Corresponding 4th component carries out power operation in the color model triple channel.

In one embodiment, described device further include:

Second processing module is used for before carrying out Fuzzy Processing to the target image, will be in the target image The pixel value of each pixel is normalized.

According to the third aspect of an embodiment of the present disclosure, a kind of image processing apparatus is provided, comprising:

Processor；

Memory for storage processor executable instruction；

Wherein, the processor is configured to:

The technical scheme provided by this disclosed embodiment can include the following benefits:

The technical scheme provided by this disclosed embodiment, to image carry out Fuzzy Processing when, can be to Fuzzy Processing after Image carry out saturation degree compensation, so that the color of the image after Fuzzy Processing is more bright-coloured, the image after avoiding Fuzzy Processing Color can become very light, meanwhile, can suitably reduce the image after Fuzzy Processing to specific luminance so that after Fuzzy Processing The brightness of image is softer, and the brightness of the image after avoiding Fuzzy Processing is enhanced too much, to reduce as far as possible fuzzy The distortion factor of treated image, greatlys improve the visual experience of user, so that the image after Fuzzy Processing does not allow as far as possible User generates false feeling.

It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not The disclosure can be limited.

Detailed description of the invention

The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure Example, and together with specification for explaining the principles of this disclosure.

Fig. 1 is a kind of flow chart of image processing method shown according to an exemplary embodiment.

Fig. 2 is the flow chart of another image processing method shown according to an exemplary embodiment.

Fig. 3 is the flow chart according to another image processing method shown in an exemplary embodiment one.

Fig. 4 is the flow chart according to another image processing method shown in an exemplary embodiment one.

Fig. 5 is the flow chart according to another image processing method shown in an exemplary embodiment one.

Fig. 6 is a kind of block diagram of image processing apparatus shown according to an exemplary embodiment.

Fig. 7 is the block diagram of another image processing apparatus shown according to an exemplary embodiment.

Fig. 8 is the block diagram of another image processing apparatus shown according to an exemplary embodiment.

Fig. 9 is the block diagram of another image processing apparatus shown according to an exemplary embodiment.

Figure 10 is the block diagram of another image processing apparatus shown according to an exemplary embodiment.

Figure 11 is the block diagram shown according to an exemplary embodiment suitable for image processing apparatus.

Specific embodiment

Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment Described in embodiment do not represent all implementations consistent with this disclosure.On the contrary, they be only with it is such as appended The example of the consistent device and method of some aspects be described in detail in claims, the disclosure.

Currently, more excellent in order to make to shoot the image quality come, user can all use substantially various image processing softwares into Row mill skin processing, and in the related technology mill skin operation in common mill skin algorithm be essentially all by using averagely after picture The pixel value of the pixel value substitution current pixel point of vegetarian refreshments operates to complete the mill skin of image, and after the operation of above-mentioned mill skin For the mill skin image arrived for original image, the color of image after mill skin operation can be thin out, and grinds the image after skin operation Brightness improves very much, will cause the feeling of whiting, so as to cause the image fault after mill skin, greatly reduces the vision body of user It tests, so that the image after mill skin can allow user to generate false feeling.

In order to solve the above-mentioned technical problem, the embodiment of the present disclosure provides a kind of image processing method, and this method can be used for In image processing program, system or device, and the corresponding executing subject of this method can be the terminal of user's carrying, such as Fig. 1 institute Show, the method comprising the steps of S101 to step S104:

In step s101, target image to be processed is subjected to Fuzzy Processing, with the target image after being obscured Each pixel corresponding first component on three channels of color model.

Fuzzy Processing is carried out to the target image to be processed, mill skin processing exactly is carried out to the target image.

Color model includes rgb color mode, and rgb color mode is a kind of color standard of industry, is respectively represented Red (R), green (G), blue channel (B), thus, three channels of color model are respectively the channel R, the channel G, channel B.

Since pixel value of each pixel in RGB triple channel is the component and channel B in component by the channel R, the road G Component is constituted, thus, each pixel corresponding first component in color model triple channel is also each pixel in color Pixel value components in model triple channel, and " how many " of the value of R, G, B just refer to brightness, thus, each pixel is in color Corresponding first component is also that each pixel after Fuzzy Processing is bright on tri- channels R, G, B respectively in model triple channel Spend component；

In addition, it is necessary to explanation: the first component is to each pixel obtained after Fuzzy Processing respectively in R, G, B tri- The general designation of luminance component on a channel, in order to be carried out with the second component, third component and the 4th component hereinafter mentioned It distinguishes, the specific value for being not offered as luminance component of each pixel on tri- channels R, G, B is the first component, and the Two components, third component and the 4th component have similar meaning, and details are not described herein again.

In step s 102, to each pixel, corresponding first component carries out brightness tune in color model triple channel It is whole, obtain each pixel corresponding second component in color model triple channel, with improve target image to specific luminance.

By the way that corresponding first component is adjusted in color model triple channel to each pixel, difference can be increased Between pixel in color model triple channel corresponding first component difference, to improve the target figure after Fuzzy Processing Picture to specific luminance.

In step s 103, to each pixel, corresponding second component carries out saturation degree benefit in color model triple channel It repays, to improve the saturation degree of target image.

It, can be right by the way that each pixel, corresponding second component carries out saturation degree compensation in color model triple channel Each pixel corresponding second component in color model triple channel is adjusted, and to improve the saturation degree of target image, is made The color of target image after obtaining Fuzzy Processing is more bright-coloured, and the color of the target image after avoiding Fuzzy Processing can become very It is light.

In step S104, to saturation degree compensation after each pixel in color model triple channel corresponding component Carry out brightness reduce adjustment, with reduce target image to specific luminance.

By each pixel after compensating saturation degree, corresponding component carries out brightness in color model triple channel Adjustment is reduced, difference of the different pixels point in color model triple channel between corresponding component can be suitably reduced, thus suitable When reduce target image to specific luminance so that the brightness of the target image after Fuzzy Processing is softer, true, avoid obscuring The brightness of treated target image is enhanced feeling that is too many and causing whiting, thus after reducing Fuzzy Processing as far as possible The distortion factor of target image greatlys improve the visual experience of user, so that the target image after Fuzzy Processing does not allow as far as possible User generates false feeling.

As shown in Fig. 2, in one embodiment, above-mentioned step S101 shown in FIG. 1 may include step A1 to step A3:

In step A1, target image is subjected to Fuzzy Processing, each pixel of the target image after being obscured exists First pixel value components in default channel, wherein the first pixel value components are used to characterize each picture of the target image after obscuring Brightness of the vegetarian refreshments on default channel；

Default channel may include one in color model triple channel or three channels or color space (YUV) In one or three channels, wherein color space triple channel is a kind of color coding staff used by eurovision system Method (belongs to PAL), and luminance signal Y and carrier chrominance signal U, V be separation, and the target image can be character image or Landscape image etc..

And when default channel includes the channel G in color model triple channel, each pixel of the target image after obscuring Pixel value components of each pixel of the point after first pixel value components in default channel are Fuzzy Processing on the channel G namely Luminance component of each pixel on the channel G after Fuzzy Processing.

In step A2, according to each pixel before the first pixel value components and Fuzzy Processing of each pixel pre- If the original pixel value component on channel, second pixel value components of each pixel on default channel are obtained, wherein second Pixel value components are used to characterize to be obtained by the original pixel value component of the first pixel value components and each pixel on default channel To brightness of each pixel on default channel；

Due to grinding the first pixel value components and its original pixel value component of each pixel obtained after skin for the first time Pixel difference is smaller, thus, it, can be according to the first pixel value components and original pixels of each pixel in order to increase the pixel difference Value component further obtains each pixel and presets the second pixel value components on channel at this, thus to before Fuzzy Processing with The pixel difference of each pixel is stretched later, increases the pixel between the second pixel value components and its original pixel value component Difference, convenient for the image after raising Fuzzy Processing to specific luminance.

In step A3, according to the second pixel value components of each pixel, each pixel is obtained in color model Corresponding first component on three channels.

Each pixel is being obtained in the second pixel value components on default channel, it can be according to the of each pixel Two pixel value components obtain each pixel corresponding first component on three channels of color model, i.e., after Fuzzy Processing Each pixel luminance component on tri- channels R, G, B respectively.

In one embodiment, the step A1 in above-mentioned Fig. 2 can be performed as:

According to each pixel in the reference zone where the original pixel value component and each pixel on default channel Each of original pixel value component of other pixels on default channel, obtain the first pixel value point of each pixel Amount, wherein default channel includes: the channel G in color model triple channel, alternatively, the channel Y in color space triple channel.

When obtaining the first pixel value components of each pixel, data can be reduced by only obtaining the component on a channel Processing difficulty reduces data processing time and improves data processing speed；And due to the pixel value components on the channel G or the channel Y Influence whether the pixel value components on tri- channels R, G, B, thus, by obtaining the first pixel on the channel G or the channel Y Be worth component, can ensure as far as possible each pixel in color model triple channel the precision of corresponding first component it is same When, reduce the computation complexity of pixel value components.

In one embodiment, above-mentioned steps " according to original pixel value component of each pixel on default channel and Original pixel value component of other pixels of each of reference zone where each pixel on default channel, obtains every First pixel value components of a pixel " can be performed as:

According to the first default Fuzzy Processing function, original pixel value component of each pixel on default channel is carried out Fuzzy Processing obtains first pixel value components of each pixel on default channel, wherein the first default Fuzzy Processing function Include:

Wherein, reference zone is the square area put centered on each pixel, and the side length of square area is packet Containing the occupied length of+1 pixel of 2 γ including each pixel, wherein in the target image between neighbor pixel Horizontal spacing and longitudinal pitch are identical, can be d expression, thus, the side length of the square area is (2 γ+1) * d, should Reference zone is centered on the corresponding current pixel point of x1, and the corresponding current pixel point of x1 can successively indicate each pixel Point, in addition, i=1 can indicate first pixel in the upper left corner of the square area, i=(2 γ+1)²It can indicate this The last one pixel in the lower right corner of square area；

Y indicates preset pixel value threshold value, and Y can be previously set,

x₁Indicate original pixel value component of each pixel on default channel,

x_iOriginal pixel value component of other pixels on default channel each of in expression square area,

X indicates first pixel value components of each pixel on default channel.

When obtaining the first pixel value components of each pixel, data can be reduced by only obtaining the component on a channel Processing difficulty reduces data processing time and improves data processing speed；And due to the pixel value components on the channel G or the channel Y Influence whether the pixel value components on tri- channels R, G, B, thus, it can be quasi- by the above-mentioned first default Fuzzy Processing function The first pixel value components on the channel G and the channel Y really are obtained, and then each pixel can ensured as far as possible in color mould In type triple channel while the precision of corresponding first component, the computation complexity of pixel value components is reduced.

In addition, not only can choose calculating each pixel in the first pixel value components on default channel with every The square area put centered on a pixel is reference zone, it is also an option that the circle put centered on each pixel Domain or other regular polygon regions etc. are reference zone.

As shown in figure 3, in one embodiment, the step A2 in above-mentioned Fig. 2 may include step S301 to step S305:

In step S301, according to the first preset formula in the second default Fuzzy Processing function, obtain Fuzzy Processing it Preceding each pixel is in the first pixel value of original pixel value component and each pixel on default channel on default channel The initial pixel of component is poor, wherein the second default Fuzzy Processing function includes: the first preset formula and the second preset formula；

In step s 302, it is poor to determine whether initial pixel difference is less than presetted pixel, wherein when the pixel of each pixel When value is normalized, which can be 0.5；

In step S303, when initial pixel difference is less than presetted pixel difference, the first public affairs in the second preset formula are executed Formula；

In step s 304, it when initial pixel difference is greater than or equal to presetted pixel difference, executes in the second preset formula Second formula；

The second preset formula N is being executed after, obtained final pixel difference is substituted into the first preset formula, is obtained every Second pixel value components of a pixel on default channel, wherein N is the positive integer more than or equal to 1, in addition, it is necessary to say It is bright:

After the initial pixel difference highPass that will be obtained for the first time according to the first preset formula substitutes into the second preset formula, meeting An intermediate pixel difference highPass is obtained, it is poor will to obtain an intermediate pixel for time second preset formula of every execution later HighPass, thus, N number of intermediate pixel difference highPass can be obtained by executing N all over the second preset formulas, and n-th intermediate pixel Poor highPass is that final pixel is poor, while preceding N-1 intermediate pixel difference highPass can continuous circulation step S303 and step Rapid S304 is executed that is, when i-th of intermediate pixel difference highPass in this N-1 intermediate pixel difference is less than presetted pixel difference The first formula in second preset formula when being greater than or equal to presetted pixel difference, executes the second formula in the second preset formula,

First preset formula:

HighPass=x₁-x

The first formula in second preset formula:

HighPass=2.0*highPass*highPass

The second formula in second preset formula:

HighPass=1-2.0* (1-highPass) * (1-highPass)

Wherein, x₁Indicate that original pixel value component of each pixel on default channel, highPass indicate initial picture Plain difference or final pixel are poor,

When obtaining initial pixel difference highPass according to the first preset formula for the first time, x indicates the first picture of each pixel Element value component,

In step S305, is executing the second preset formula N times, obtained final pixel difference highPass is substituted into first After preset formula, obtained x indicates the second pixel value components of each pixel.

It is (i.e. initial that initial highPass is obtained in the original pixel value component using the first preset formula and each pixel Pixel difference) after, it can be determined that it is poor whether the initial pixel difference is less than the presetted pixel, if it is poor to be less than the presetted pixel, holds The first formula in the second preset formula of row, it is poor if more than or equal to the presetted pixel, then it executes and states in the second preset formula Second formula, the intermediate pixel difference obtained later can also recycle in the manner described above executes the second preset formula, to obtain Final pixel is poor, and then obtained final pixel difference is substituted into first preset formula, can be obtained smoothed out each picture Vegetarian refreshments presets the second pixel value components on channel at this；

Wherein, the numerical value of N is bigger, the second pixel value components of obtained each pixel and point of original pixel value component It is bigger to measure difference, later period Fuzzy Processing (i.e. mill skin) degree is deeper, the target image after obtained Fuzzy Processing to specific luminance Also higher.

As shown in figure 4, in one embodiment, above-mentioned step A3 shown in Fig. 2 may include step S401 and step S402:

In step S401, by the second pixel value components of each pixel successively with each pixel in target triple channel On each original pixel value component be weighted summation, obtain first object pixel of each pixel in target triple channel Value, wherein target triple channel includes: color model triple channel or color space triple channel, and no matter target triple channel is face Color model triple channel or be color space triple channel, the default channel may each be the channel Y or the channel G；

Since the pixel value components on the channel G or the channel Y influence whether the pixel value components on tri- channels R, G, B, Thus, by obtaining second pixel value components of each pixel on the channel G or the channel Y, and by each pixel at this Three pixel value components of second pixel value components as each pixel in target triple channel on default channel, respectively and Each original pixel value component of each pixel in the target triple channel is weighted summation, can reduce pixel value components Computation complexity on the basis of, obtain first object pixel of the higher each pixel of accuracy in the target triple channel Value, specific calculating process are as follows:

By taking target triple channel is color model triple channel, default channel is the channel G as an example, for Weighted Index is α, it is assumed that Each original pixel value component of some pixel in color model triple channel is R=a0, G=b0, B=c0, the i.e. pixel Original pixel value composed by each original pixel value component in color model triple channel is a0b0c0, and if second picture Element value component is G=b1, then after obtaining second pixel value components G=b1, since the pixel value components on the channel G can shadow It rings to the pixel value components on tri- channels R, G, B, thus, in order to reduce the difficulty in computation of pixel value components, directly it can incite somebody to action this Each pixel value components of the pixel in color model triple channel are accordingly to be regarded as b1, i.e., by the pixel after Fuzzy Processing in color Each pixel value components in model triple channel are considered as R=b1, G=b1, B=b1, then by the pixel in color model threeway Each pixel value components on road are weighted summation with each original pixel value component of the pixel in target triple channel respectively, Each pixel value components for obtaining the pixel in target image after Fuzzy Processing are respectively R=α * a0+ (1- α) * b1, G=α * B0+ (1- α) * b1, B=α * c0+ (1- α) * b1, the first object pixel value are (α * a0+ (1- α) * b1) (α * b0+ (1- α) * b1) (α * c0+ (1- α) * b1),

Or R=(1- α) * a0+ α * b1, G=(1- α) * b0+ α * b1, B=(1- α) * c0+ α * b1, the first object pixel Value is ((1- α) * a0+ α * b1) ((1- α) * b0+ α * b1) ((1- α) * c0+ α * b1)；

In addition, pixel value of each pixel after the disclosed acquisition Fuzzy Processing of the present embodiment in target triple channel Scheme replaces this in turn compared to directly its first object pixel value is obtained using the second pixel value components of each pixel The scheme of the original pixel value of pixel can retain while the pixel value of pixel each after obtaining Fuzzy Processing The features such as details, color, the brightness of former target image.

In step S402, according to the first object pixel value of each pixel, each pixel is obtained in color model Corresponding first component in triple channel；

According to the first object pixel value of each pixel, it is corresponding in color model triple channel can quickly to obtain it First component, such as: when first object pixel value be pixel value of each pixel in color model triple channel and this first When target pixel value is a1a2a3, corresponding first component is R=a1, G=a2, B=a3 in color model triple channel.

Step S102 in above-mentioned Fig. 1 may include step S403 and step S404:

It is corresponding in color model triple channel to each pixel according to preset image gamma value in step S403 The first component carry out power operation；Wherein, image gamma value is optimization of profile adjustment, is the miscellaneous function of brightness and contrast, The gamma adjustment that each frame picture is all fixed, the brightness and contrast of picture are greatly optimized, and image quality can also be with It has obtained greatly being promoted.

In addition, when carrying out power operation being existed using preset image gamma value as power exponent and due to each pixel Corresponding first component is the numerical value between 0~1 in color model triple channel, thus, which takes Being worth range is 0~1, in this way, after power operation, corresponding first component is just in color model triple channel for each pixel It will increase, the second component increased.

When the first component to each pixel carries out power operation, preset image gamma value can be used to each picture First component of vegetarian refreshments corresponding three luminance components (also known as pixel value components) on tri- channels R, G, B carry out power fortune respectively It calculates.

In step s 404, using each pixel obtained after power operation corresponding the in color model triple channel Two components replace power operation before each pixel in color model triple channel corresponding first component, to improve target figure Picture to specific luminance.

By the way that each pixel, corresponding first component carries out power operation in color model triple channel, and transported using power First component of each pixel before the second component replacement power operation of each pixel obtained after calculating, can make every Luminance component of a pixel in color model triple channel increases, and different pixels point is corresponding bright in color model triple channel The difference spent between component increases, with the target image after realization raising Fuzzy Processing to specific luminance.

As shown in figure 5, in one embodiment, the step S103 in above-mentioned Fig. 1 may include step S501 to step S504:

In step S501, according to each pixel obtained after power operation corresponding the in color model triple channel Two components determine the second target pixel value of each pixel；

In step S502, by each original pixel value of the second target pixel value of each pixel and each pixel point Original pixel value composed by measuring is weighted summation, obtains the third target pixel value of each pixel, wherein Weighted Index It for the numerical value between 0~1, and is by the brightness in target triple channel respectively of the second target pixel value of each pixel here Each original pixel value component of component and the pixel is weighted summation, such as: when the second object pixel of each pixel Value is R1G1B1, original pixel value composed by each original pixel value component of the pixel is R2G2B2, Weighted Index β When, the third target pixel value can for for (β * R1+ (1- β) * R2) (β * G1+ (1- β) * G2) (β * B1+ (1- β) * B2) or For ((1- β) * R1+ β * R2) ((1- β) * G1+ β * G2) ((1- β) * B1+ β * B2)；

Each pixel is being calculated in the third target pixel value in target triple channel, by by the of each pixel Original pixel value composed by two target pixel values and each original pixel value component of the pixel in target triple channel carries out Weighted sum, the not only pixel value after available Fuzzy Processing, but also the details of some former target images, color can be retained as far as possible The features such as coloured silk, brightness avoid directly replacing original pixel value using second target pixel value and causing to be lost excessive former mesh The features such as details, color, the brightness of logo image.

In step S503, according to the third target pixel value of each pixel, each pixel is obtained in color model Corresponding third component in triple channel；

In step S504, using default saturation degree matrix to each pixel corresponding in color model triple channel Three-component carries out saturation degree compensation, obtains each pixel corresponding 4th component in color model triple channel.

By using default saturation matrix, to each pixel, the corresponding third component in color model triple channel is carried out Saturation degree compensation, can to each pixel, corresponding third component is further adjusted in color model triple channel, from And the saturation degree of target image is improved, so that the color of the target image after Fuzzy Processing is more bright-coloured, avoid obscuring as far as possible Target image color that treated becomes very light.Wherein, which can be with are as follows:

Wherein, s is saturation degree coefficient, value 0~1, using default saturation degree matrix to each pixel in color model Corresponding third component carries out the specific embodiment of saturation degree compensation in triple channel are as follows:

By each pixel, corresponding third component is multiplied with the default saturation matrix in color model triple channel, Saturation degree compensation can be carried out to each pixel.

In one embodiment, the step S104 in above-mentioned Fig. 1 can be performed as:

According to the inverse of preset image gamma value, to each pixel after progress saturation degree compensation in color model Corresponding 4th component carries out power operation in triple channel, with reduce target image to specific luminance.

Since the value range of the pre-set image gamma value is 0~1, the pre-set image gamma value it is reciprocal be naturally greater than 1 numerical value, and each pixel corresponding 4th component in color model triple channel is the value between 0~1, thus, warp It crosses after power operation, each pixel corresponding 4th component (i.e. luminance component) in color model triple channel will reduce, Difference of the different pixels point in color model triple channel between corresponding luminance component can also be reduced, to reduce Fuzzy Processing The target image afterwards to specific luminance, the appropriate brightness for weakening the target image after Fuzzy Processing, so that after Fuzzy Processing The brightness of target image is softer, and then greatly improves user to the vision body of the target image after Fuzzy Processing It tests, so that the target image after Fuzzy Processing is truer, the distortion factor is smaller.

When the 4th component to each pixel carries out power operation, the inverse that preset image gamma value can be used is right 4th component of each pixel on tri- channels R, G, B corresponding three luminance components (also known as pixel value components) respectively into Row power operation.

In one embodiment, the above method may also include that

Before carrying out Fuzzy Processing to target image, the pixel value of each pixel in target image is subjected to normalizing Change processing.

To target image carry out Fuzzy Processing before, by by the pixel value of each pixel in the target image into Row normalized so that whole image processing method in the disclosure GPU (Graphics Processing Unit, Graphics processor) on carry out, greatly reduce the negative of CPU (Central Processing Unit, central processing unit) Load, improves image procossing speed, and due to and vacant cpu resource, thus, can be use up during carrying out image procossing User can be able to satisfy to the requirement of real-time of video, communication.

The above-mentioned image processing method that the corresponding embodiment of the present disclosure provides, the embodiment of the present disclosure also provide a kind of image procossing Device, as shown in fig. 6, the device includes first processing module 601, the first adjustment module 602, compensating module 603 and the second tune Mould preparation block 604:

First processing module 601 is configured as target image to be processed carrying out Fuzzy Processing, after being obscured Each pixel of target image corresponding first component on three channels of color model；

The first adjustment module 602 is configured as to each pixel corresponding first component in color model triple channel Brightness adjustment is carried out, each pixel corresponding second component in color model triple channel is obtained；

Compensating module 603 is configured as the corresponding second component progress in color model triple channel to each pixel Saturation degree compensation；

Second adjustment module 604 is configured as each pixel after compensating saturation degree in color model triple channel Upper corresponding component, which carries out brightness, reduces adjustment.

As shown in fig. 7, in one embodiment, above-mentioned first processing module 601 shown in fig. 6 may include processing submodule Block 6011, the first acquisition submodule 6012 and the second acquisition submodule 6013:

Submodule 6011 is handled, is configured as target image carrying out Fuzzy Processing, the target image after being obscured First pixel value components of each pixel in default channel, wherein the first pixel value components be configured as characterization it is fuzzy after Brightness of each pixel of target image on default channel；

First acquisition submodule 6012, be configured as according to the first pixel value components and Fuzzy Processing of each pixel it Original pixel value component of the preceding each pixel on default channel obtains second pixel of each pixel on default channel It is worth component, wherein the second pixel value components are configured as characterization by the first pixel value components and each pixel in default channel On brightness of the obtained each pixel of original pixel value component on default channel；

Second acquisition submodule 6013 is configured as the second pixel value components according to each pixel, obtains each picture Vegetarian refreshments corresponding first component on three channels of color model.

In one embodiment, processing submodule 6011 may include first acquisition unit:

First acquisition unit is configured as original pixel value component according to each pixel on default channel and each Original pixel value component of other pixels of each of reference zone where pixel on default channel, obtains each picture First pixel value components of vegetarian refreshments, wherein default channel includes: the channel G in color model (RGB) triple channel, alternatively, color The channel Y in space (YUV) triple channel.

In one embodiment, first acquisition unit includes:

Subelement is handled, is configured as according to the first default Fuzzy Processing function, to each pixel on default channel Original pixel value component carry out Fuzzy Processing, obtain first pixel value components of each pixel on default channel, wherein First default Fuzzy Processing function includes:

Wherein, reference zone is the square area put centered on each pixel, and the side length of square area is packet Containing the occupied length of+1 pixel of 2 γ including each pixel,

Y indicates preset pixel value threshold value,

x₁Indicate original pixel value component of each pixel on default channel,

X indicates first pixel value components of each pixel on default channel.

As shown in figure 8, in one embodiment, the first acquisition submodule 6012 may include second acquisition unit 60121, Determination unit 60122, the first execution unit 60123, the second execution unit 60124 and third acquiring unit 60125:

Second acquisition unit 60121 is configured as being obtained according to the first preset formula in the second default Fuzzy Processing function Take each pixel before Fuzzy Processing on default channel original pixel value component and each pixel on default channel The first pixel value components initial pixel it is poor, wherein the second default Fuzzy Processing function includes: the first preset formula and second Preset formula；

It is poor to be configured to determine that whether initial pixel difference is less than presetted pixel for determination unit 60122；

First execution unit 60123 is configured as when initial pixel difference is less than presetted pixel difference, executes the second default public affairs The first formula in formula；

Second execution unit 60124 is configured as executing second when initial pixel difference is greater than or equal to presetted pixel difference The second formula in preset formula；

Third acquiring unit 60125 is configured as executing the second preset formula N after, the final pixel that will be obtained Difference substitutes into the first preset formula, obtains second pixel value components of each pixel on default channel, wherein N be greater than Or the positive integer equal to 1,

First preset formula:

HighPass=x₁-x

The first formula in second preset formula:

HighPass=2.0*highPass*highPass

The second formula in second preset formula:

HighPass=1-2.0* (1-highPass) * (1-highPass)

After executing the second preset formula N times, obtained final pixel difference highPass substituted into the first preset formula, X indicates the second pixel value components of each pixel.

In one embodiment, the second acquisition submodule 6013 may include summation unit, the 4th acquiring unit:

Summation unit is configured as the second pixel value components of each pixel successively with each pixel in target three Each original pixel value component on channel is weighted summation, obtains first object picture of each pixel in target triple channel Element value, wherein target triple channel includes: color model triple channel or color space triple channel；

4th acquiring unit is configured as the first object pixel value according to each pixel, obtains each pixel and exists Corresponding first component in color model triple channel；

The first adjustment module 602 may include the first operation submodule and replacement submodule:

First operation submodule is configured as according to preset image gamma value, to each pixel in color model three Corresponding first component carries out power operation on channel；

Submodule is replaced, it is right in color model triple channel to be configured with each pixel obtained after power operation Answer second component replacement power operation before each pixel in color model triple channel corresponding first component.

As shown in figure 9, in one embodiment, above-mentioned compensating module 604 shown in fig. 6 can include determining that submodule 6041, third acquisition submodule 6042, the 4th acquisition submodule 6043 and compensation submodule 6044:

It determines submodule 6041, is configured as according to each pixel obtained after power operation in color model triple channel Upper corresponding second component, determines the second target pixel value of each pixel；

Third acquisition submodule 6042 is configured as the second target pixel value of each pixel and each pixel Original pixel value composed by each original pixel value component is weighted summation, obtains the third object pixel of each pixel Value；

4th acquisition submodule 6043 is configured as the third target pixel value according to each pixel, obtains each picture Vegetarian refreshments corresponding third component in color model triple channel；

Submodule 6044 is compensated, is configured with default saturation degree matrix to each pixel in color model triple channel Upper corresponding third component carries out saturation degree compensation, obtains each pixel corresponding 4th point in color model triple channel Amount.

In one embodiment, second adjustment module 604 may include the second operation submodule:

Second operation submodule is configured as the inverse according to preset image gamma value, to each pixel in color Corresponding 4th component carries out power operation in model triple channel.

As shown in Figure 10, in one embodiment, above-mentioned device shown in fig. 6 may also include Second processing module 1001:

Second processing module 1001 is configured as before carrying out Fuzzy Processing to target image, will be in target image The pixel value of each pixel is normalized.

Processor；

Memory for storage processor executable instruction；

Wherein, processor is configured as:

Above-mentioned processor is also configured to:

It is described that target image to be processed is subjected to Fuzzy Processing, with each picture of the target image after being obscured Vegetarian refreshments corresponding first component on three channels of color model, comprising:

Above-mentioned processor is also configured to:

Described that the target image is carried out Fuzzy Processing, each pixel of the target image after being obscured exists First pixel value components in default channel, comprising:

Above-mentioned processor is also configured to:

The original pixel value component according to each pixel on the default channel and each pixel Each of reference zone where point original pixel value component of other pixels on the default channel obtains described every First pixel value components of a pixel, comprising:

Y indicates preset pixel value threshold value,

X indicates first pixel value components of each pixel on the default channel.

Above-mentioned processor is also configured to:

First pixel value components and each pixel of the Fuzzy Processing foregoing description according to each pixel Original pixel value component of the point on the default channel obtains second picture of each pixel on the default channel Element value component, comprising:

First preset formula:

HighPass=x₁-x

First formula in second preset formula:

HighPass=2.0*highPass*highPass

Second formula in second preset formula:

HighPass=1-2.0* (1-highPass) * (1-highPass)

Above-mentioned processor is also configured to:

Second pixel value components according to each pixel obtain each pixel in color mould Corresponding first component in type triple channel, comprising:

Above-mentioned processor is also configured to:

It is described that each pixel, corresponding second component carries out saturation degree benefit in the color model triple channel It repays, comprising:

Above-mentioned processor is also configured to:

It is described to saturation degree compensation after each pixel in the color model triple channel corresponding component Carrying out brightness reduces adjustment, comprising:

Above-mentioned processor is also configured to:

The method also includes:

Figure 11 is a kind of block diagram for image processing apparatus 1100 shown according to an exemplary embodiment, and the device is suitable For terminal device.For example, device 1100 can be mobile phone, computer, digital broadcasting terminal, messaging device, trip Play console, tablet device, Medical Devices, body-building equipment, a number assistant etc..

Referring to Fig.1 1, device 1100 may include with next or at least two components: processing component 1102, memory 1104, power supply module 1106, multimedia component 1108, audio component 1110, the interface 1112 of input/output (I/O), sensor Component 1114 and communication component 1116.

The integrated operation of the usual control device 1100 of processing component 1102, such as with display, telephone call, data communication, Camera operation and record operate associated operation.Processing component 1102 may include one or at least two processors 1120 It executes instruction, to perform all or part of the steps of the methods described above.In addition, processing component 1102 may include one or at least Two modules, convenient for the interaction between processing component 1102 and other assemblies.For example, processing component 1102 may include multimedia Module, to facilitate the interaction between multimedia component 1108 and processing component 1102.

Memory 1104 is configured as storing various types of data to support the operation in device 1100.These data Example includes the instruction for any storage object or method that operate on device 1100, contacts user data, telephone directory number According to, message, picture, video etc..Memory 1104 can by any kind of volatibility or non-volatile memory device or it Combination realize, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM) is erasable Except programmable read only memory (EPROM), programmable read only memory (PROM), read-only memory (ROM), magnetic memory, fastly Flash memory, disk or CD.

Power supply module 1106 provides power supply for the various assemblies of device 1100.Power supply module 1106 may include power management System, one or at least two power supplys and other with for device 1100 generate, manage, and distribute the associated component of power supply.

Multimedia component 1108 includes the screen of one output interface of offer between described device 1100 and user.? In some embodiments, screen may include liquid crystal display (LCD) and touch panel (TP).If screen includes touch panel, Screen may be implemented as touch screen, to receive input signal from the user.Touch panel includes one or at least two touchings Sensor is touched to sense the gesture on touch, slide, and touch panel.The touch sensor can not only sense touch or cunning The boundary of movement, but also detect duration and pressure associated with the touch or slide operation.In some embodiments In, multimedia component 1108 includes a front camera and/or rear camera.When device 1100 is in operation mode, such as When screening-mode or video mode, front camera and/or rear camera can receive external multi-medium data.Before each Setting camera and rear camera can be a fixed optical lens system or has focusing and optical zoom capabilities.

Audio component 1110 is configured as output and/or input audio signal.For example, audio component 1110 includes a wheat Gram wind (MIC), when device 1100 is in operation mode, when such as call mode, recording mode, and voice recognition mode, microphone quilt It is configured to receive external audio signal.The received audio signal can be further stored in memory 1104 or via communication Component 1116 is sent.In some embodiments, audio component 1110 further includes a loudspeaker, is used for output audio signal.

I/O interface 1112 provides interface, above-mentioned peripheral interface module between processing component 1102 and peripheral interface module It can be keyboard, click wheel, button etc..These buttons may include, but are not limited to: home button, volume button, start button and Locking press button.

Sensor module 1114 includes one or at least two sensors, for providing the shape of various aspects for device 1100 State assessment.For example, sensor module 1114 can detecte the state that opens/closes of device 1100, the relative positioning of component, example Such as the display and keypad that the component is device 1100, sensor module 1114 can be with detection device 1100 or device The position change of 1100 1 components, the existence or non-existence that user contacts with device 1100,1100 orientation of device or acceleration/subtract The temperature change of speed and device 1100.Sensor module 1114 may include proximity sensor, be configured to not any Physical contact when detect the presence of nearby objects.Sensor module 1114 can also include optical sensor, as CMOS or CCD schemes As sensor, for being used in imaging applications.In some embodiments, which can also include acceleration Sensor, gyro sensor, Magnetic Sensor, pressure sensor or temperature sensor.

Communication component 1116 is configured to facilitate the communication of wired or wireless way between device 1100 and other equipment.Dress The wireless network based on communication standard, such as WiFi can be accessed by setting 1100,2G or 3G or their combination.It is exemplary at one In embodiment, communication component 1116 receives broadcast singal or broadcast correlation from external broadcasting management system via broadcast channel Information.In one exemplary embodiment, the communication component 1116 further includes near-field communication (NFC) module, to promote short distance Communication.For example, radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra wide band can be based in NFC module (UWB) technology, bluetooth (BT) technology and other technologies are realized.

In the exemplary embodiment, device 1100 can by one or at least two application specific integrated circuits (ASIC), Digital signal processor (DSP), digital signal processing appts (DSPD), programmable logic device (PLD), field-programmable gate array It arranges (FPGA), controller, microcontroller, microprocessor or other electronic building bricks to realize, for executing the above method.

In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instruction, example are additionally provided It such as include the memory 1104 of instruction, above-metioned instruction can be executed by the processor 1120 of device 1100 to complete the above method.Example Such as, the non-transitorycomputer readable storage medium can be ROM, random access memory (RAM), CD-ROM, tape, soft Disk and optical data storage devices etc..

A kind of non-transitorycomputer readable storage medium, when the instruction in the storage medium is by above-mentioned apparatus 1100 When processor executes, so that above-mentioned apparatus 1100 is able to carry out a kind of image processing method, comprising:

Y indicates preset pixel value threshold value,

X indicates first pixel value components of each pixel on the default channel.

First preset formula:

HighPass=x₁-x

First formula in second preset formula:

HighPass=2.0*highPass*highPass

Second formula in second preset formula:

HighPass=1-2.0* (1-highPass) * (1-highPass)

In one embodiment, the method also includes:

Art technology user person will readily occur to the disclosure after considering specification and practicing disclosure disclosed herein Other embodiments.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes Or adaptive change follow the general principles of this disclosure and including the disclosure it is undocumented in the art known in often Knowledge or conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by following Claim point out.

It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by the accompanying claims.

Claims

1. a kind of image processing method characterized by comprising

Target image to be processed is subjected to Fuzzy Processing, with each pixel of the target image after being obscured in face Corresponding first component on three channels of color model；

To each pixel, corresponding first component carries out brightness adjustment in the color model triple channel, obtains described Each pixel corresponding second component in the color model triple channel；

To each pixel after saturation degree compensation, corresponding component carries out brightness in the color model triple channel Reduce adjustment；

It is described that target image to be processed is subjected to Fuzzy Processing, with each pixel of the target image after being obscured Corresponding first component on three channels of color model, comprising:

The target image is subjected to Fuzzy Processing, each pixel of the target image after being obscured is in default channel The first pixel value components, wherein first pixel value components be used to characterize it is fuzzy after the target image each picture Brightness of the vegetarian refreshments on the default channel；

According to first pixel value components of each pixel and each pixel of the Fuzzy Processing foregoing description described Original pixel value component on default channel obtains each pixel the second pixel value on the default channel point Amount, wherein second pixel value components are for characterizing by first pixel value components and each pixel described Brightness of each pixel that original pixel value component on default channel obtains on the default channel；

According to second pixel value components of each pixel, each pixel is obtained at three of color model Corresponding first component on channel.

2. the method according to claim 1, wherein

Described that the target image is carried out Fuzzy Processing, each pixel of the target image after being obscured is default First pixel value components in channel, comprising:

According to each pixel where the original pixel value component and each pixel on the default channel Original pixel value component of other pixels of each of reference zone on the default channel, obtains each pixel First pixel value components, wherein the default channel includes: the channel G in the color model RGB triple channel, or Person, the channel Y in color space YUV triple channel.

3. according to the method described in claim 2, it is characterized in that,

The original pixel value component according to each pixel on the default channel and each pixel institute Each of reference zone original pixel value component of other pixels on the default channel, obtain each picture First pixel value components of vegetarian refreshments, comprising:

According to the first default Fuzzy Processing function, to original pixel value component of each pixel on the default channel Fuzzy Processing is carried out, obtains first pixel value components of each pixel on the default channel, wherein described First default Fuzzy Processing function includes:

Wherein, the reference zone is the square area put centered on each pixel, the square area Side length be comprising the occupied length of+1 pixel of 2 γ including each pixel,

Y indicates preset pixel value threshold value,

x_iIndicate each original pixel value component of other pixels on the default channel in square area,

X indicates first pixel value components of each pixel on the default channel.

4. the method according to claim 1, wherein

It is described to be existed according to first pixel value components and each pixel of the Fuzzy Processing foregoing description of each pixel Original pixel value component on the default channel obtains second pixel value of each pixel on the default channel Component, comprising:

According to the first preset formula in the second default Fuzzy Processing function, obtains each pixel of the Fuzzy Processing foregoing description and exist First pixel of original pixel value component and each pixel on the default channel on the default channel The initial pixel for being worth component is poor, wherein the second default Fuzzy Processing function includes: that first preset formula and second are pre- If formula；

When the initial pixel difference is less than the presetted pixel difference, the first formula in second preset formula is executed；

When the initial pixel difference is greater than or equal to the presetted pixel difference, the second public affairs in second preset formula are executed Formula；

The second preset formula N is being executed after, obtained final pixel difference is substituted into first preset formula, is obtained Obtaining second pixel value components of each pixel on the default channel, wherein N is the positive integer more than or equal to 1,

First preset formula:

HighPass=x₁-x

First formula in second preset formula:

HighPass=2.0*highPass*highPass

Second formula in second preset formula:

HighPass=1-2.0* (1-highPass) * (1-highPass)

Wherein, x₁Indicate that the original pixel value component of each pixel on the default channel, highPass indicate The initial pixel difference or the final pixel are poor,

When obtaining the initial pixel difference highPass according to first preset formula for the first time, the x indicates each picture First pixel value components of vegetarian refreshments,

Execute the second preset formula N all over, obtained final pixel difference highPass substituted into first preset formula Later, the x indicates second pixel value components of each pixel.

5. method according to claim 1 to 4, which is characterized in that

Second pixel value components according to each pixel obtain each pixel in color model three Corresponding first component on channel, comprising:

By second pixel value components of each pixel successively with each pixel in target triple channel Each original pixel value component is weighted summation, obtains first object picture of each pixel in the target triple channel Element value, wherein the target triple channel includes: the color model triple channel or color space triple channel；

According to the first object pixel value of each pixel, each pixel is obtained in the color model three Corresponding first component on channel；

It is described that each pixel, corresponding first component carries out brightness adjustment, packet in the color model triple channel It includes:

According to preset image gamma value, to each pixel in the color model triple channel corresponding first component Carry out power operation；

Using each pixel obtained after power operation, corresponding second component is replaced in the color model triple channel Each pixel before changing power operation corresponding first component in the color model triple channel.

6. according to the method described in claim 5, it is characterized in that,

It is described that each pixel, corresponding second component carries out saturation degree compensation, packet in the color model triple channel It includes:

The each pixel obtained later according to power operation corresponding second component in the color model triple channel, really Second target pixel value of fixed each pixel；

By each original pixel value component institute of second target pixel value of each pixel and each pixel The original pixel value of composition is weighted summation, obtains the third target pixel value of each pixel；

According to the third target pixel value of each pixel, each pixel is obtained in the color model three Corresponding third component on channel；

Using default saturation degree matrix to each pixel in the color model triple channel corresponding third component into The compensation of row saturation degree, obtains each pixel corresponding 4th component in the color model triple channel.

7. according to the method described in claim 6, it is characterized in that,

Each pixel corresponding component progress in the color model triple channel after the compensation to saturation degree Brightness reduces adjustment, comprising:

It is corresponding in the color model triple channel to each pixel according to the inverse of the preset image gamma value The 4th component carry out power operation.

8. method according to claim 1 to 4, which is characterized in that the method also includes:

Before carrying out Fuzzy Processing to the target image, the pixel value of each pixel in the target image is carried out Normalized.

9. a kind of image processing apparatus characterized by comprising

First processing module, for target image to be processed to be carried out Fuzzy Processing, with the target figure after being obscured Each pixel of picture corresponding first component on three channels of color model；

The first adjustment module, for corresponding first component to carry out in the color model triple channel to each pixel Brightness adjustment obtains each pixel corresponding second component in the color model triple channel；

Compensating module, for corresponding second component to be saturated in the color model triple channel to each pixel Degree compensation；

Second adjustment module is right in the color model triple channel for each pixel after compensating saturation degree The component answered, which carries out brightness, reduces adjustment；

The first processing module includes:

Submodule is handled, for the target image to be carried out Fuzzy Processing, each of described target image after being obscured First pixel value components of the pixel in default channel, wherein first pixel value components are used to characterize described after obscuring Brightness of each pixel of target image on the default channel；

First acquisition submodule, for institute before first pixel value components and Fuzzy Processing according to each pixel Original pixel value component of each pixel on the default channel is stated, obtains each pixel in the default channel On the second pixel value components, wherein second pixel value components are for characterizing by first pixel value components and described Each pixel that original pixel value component of each pixel on the default channel obtains is in the default channel On brightness；

Second acquisition submodule obtains each picture for second pixel value components according to each pixel Vegetarian refreshments corresponding first component on three channels of color model.

10. device according to claim 9, which is characterized in that

The processing submodule includes:

First acquisition unit, for according to original pixel value component of each pixel on the default channel and described Original pixel value component of other pixels of each of reference zone where each pixel on the default channel, obtains To first pixel value components of each pixel, wherein the default channel includes: the color model RGB tri- The channel G in channel, alternatively, the channel Y in color space YUV triple channel.

11. device according to claim 10, which is characterized in that

The first acquisition unit includes:

Subelement is handled, is used for according to the first default Fuzzy Processing function, to each pixel on the default channel Original pixel value component carry out Fuzzy Processing, obtain first pixel of each pixel on the default channel It is worth component, wherein the first default Fuzzy Processing function includes:

Y indicates preset pixel value threshold value,

X indicates first pixel value components of each pixel on the default channel.

12. device according to claim 9, which is characterized in that

First acquisition submodule includes:

Second acquisition unit, for according to the first preset formula in the second default Fuzzy Processing function, obtain Fuzzy Processing it Original pixel value component and each pixel of the preceding each pixel on the default channel are described default logical The initial pixel of first pixel value components on road is poor, wherein the second default Fuzzy Processing function includes: described One preset formula and the second preset formula；

First execution unit, for when the initial pixel difference is less than the presetted pixel difference, executing the described second default public affairs The first formula in formula；

Second execution unit, for executing described second when the initial pixel difference is greater than or equal to the presetted pixel difference The second formula in preset formula；

Third acquiring unit will be described in the substitution of obtained final pixel difference for executing the second preset formula N after In first preset formula, second pixel value components of each pixel on the default channel are obtained, wherein N is big In or equal to 1 positive integer,

First preset formula:

HighPass=x₁-x

First formula in second preset formula:

HighPass=2.0*highPass*highPass

Second formula in second preset formula:

HighPass=1-2.0* (1-highPass) * (1-highPass)

13. the device according to any one of claim 9 to 12, which is characterized in that

Second acquisition submodule includes:

Summation unit, for by second pixel value components of each pixel successively with each pixel in mesh Each original pixel value component in mark triple channel is weighted summation, obtains each pixel in the target triple channel First object pixel value, wherein the target triple channel includes: the color model triple channel or color space threeway Road；

4th acquiring unit obtains each pixel for the first object pixel value according to each pixel Point corresponding first component in the color model triple channel；

The first adjustment module includes:

First operation submodule is used for according to preset image gamma value, to each pixel in the color model three Corresponding first component carries out power operation on channel；

Submodule is replaced, for right in the color model triple channel using each pixel obtained after power operation Each pixel before the second component replacement power operation answered is corresponding first point in the color model triple channel Amount.

14. device according to claim 13, which is characterized in that

The compensating module includes:

Submodule is determined, for right in the color model triple channel according to each pixel obtained after power operation The second component answered determines the second target pixel value of each pixel；

Third acquisition submodule, for by second target pixel value of each pixel and each pixel Original pixel value composed by each original pixel value component is weighted summation, obtains the third target picture of each pixel Element value；

4th acquisition submodule obtains each picture for the third target pixel value according to each pixel Vegetarian refreshments corresponding third component in the color model triple channel；

Submodule is compensated, for right in the color model triple channel to each pixel using default saturation degree matrix The third component answered carries out saturation degree compensation, obtains each pixel the corresponding 4th in the color model triple channel Component.

15. device according to claim 14, which is characterized in that

The second adjustment module includes:

Second operation submodule, for the inverse according to the preset image gamma value, to each pixel described Corresponding 4th component carries out power operation in color model triple channel.

16. the device according to any one of claim 9 to 12, which is characterized in that described device further include:

Second processing module is used for before carrying out Fuzzy Processing to the target image, by each of described target image The pixel value of pixel is normalized.

17. a kind of non-transitorycomputer readable storage medium, is stored thereon with computer program, which is characterized in that the journey The step of any one of claims 1 to 8 the method is realized when sequence is executed by processor.