CN102800060B - The quick self-adapted optimization method of digital picture under low-light (level) - Google Patents

Abstract

The quick self-adapted optimization method of digital picture under a kind of low-light (level), comprise the following steps: that (one) selects the digital picture obtaining under low-light (level) is source images, obtain the chromatic value of three kinds of components of the each pixel red, green, blue of source images, make the colourity spectrum of three kinds of components of red, green, blue, and calculate the mean flow rate of source images; (2) standardized images of generation source images; (3) standardized images is carried out to quick optimization, obtain optimization image. The invention has the beneficial effects as follows: not needing just can be according to the mean flow rate of original image through Multiple-Scan, realize adaptively the optimization of low-light (level) digital picture, save the processing time greatly, realize the optimized real-time processing of digital picture quality, be effectively applied to field of video processing.

Description

The quick self-adapted optimization method of digital picture under low-light (level)

Technical field

The invention belongs to technical field of image processing, is to utilize Zadeh-X transform method quick adaptivelyObtain the method for the best in qualityization digital picture.

Background technology

People, in the time using photography and vedio recording equipment, generally wish to obtain image the best in quality. ButSeldom method relates to the best in qualityization of coloured image. Before the inventor, propose one and obtained qualityThe preferably method (patent No.: ZL200910190834.2) of coloured image, can be by scanning Zadeh-XThe value of the transformation parameter Delta of conversion, to obtain the maximum of color image quality evaluation functions NCAF, is comeObtain best quality image corresponding to original color image. But the method need to change Zadeh-X one by oneThe value of the transformation parameter Delta of conversion realizes, and length consuming time, is unfavorable for the real-time processing of coloured image,Can not be used for video field.

Summary of the invention

The object of this invention is to provide one and can realize rapidly, adaptively low-light (level) digital picture the bestThe method of changing.

To achieve the object of the present invention, it is quick self-adapted that the present invention proposes under a kind of low-light (level) digital pictureGoodization method, its key is to comprise the following steps:

Step 1: selecting the digital picture obtaining under low-light (level) is source images S, obtains the each picture of source images SChromatic value R (x, y), G (x, y), the B (x, y) of three kinds of components of red, green, blue of vegetarian refreshments, make red, green,The colourity of blue three kinds of components is composed, and calculates the brightness value L (x, y) of each pixel, obtains source images S'sMean flow rate AL;

Colourity spectrum can be according to Chinese patent " for the height of the gradation of image/chrominance information of bottom layer image miningResolved detection method " (patent No.: the method 200610054324.9) is carried out is used the method to obtainColourity is composed, and can obtain having the high-resolution colourity spectrum of a gamut of chromaticities, is more conducive in step 2Determining of boundary value.

The mean flow rate AL of source images S calculates by following formula:

$AL=\frac{1}{M\×N}\underset{y=0}{\overset{N-1}{\Σ}}\underset{x=0}{\overset{M-1}{\Σ}}L(x,y)$

Wherein, L (x, y) is the brightness value of source images S pixel (x, y), M, N be source images S X,Pixel count in Y-direction.

The brightness value L (x, y) of pixel (x, y) can be by three kinds points of this pixel (x, y) red, green, bluesChromatic value R (x, y), G (x, y), the B (x, y) of amount calculate according to following formula:

$L(x,y)=\frac{1}{\sqrt{3}}(\sqrt{R^2(x\·y)+G^2(x,y)+B^2(x,y)}$

In formula,For domain of definition constraint constant, L (x, y) is changed in [0,255].

Processing of the present invention be the digital picture of obtaining under low-light (level), therefore AL≤127.5.

Step 2: generate the standardized images B of source images S, standardized images B obtains by the following method:

(1) search for respectively three kinds of component colourities of source images S red, green, blue spectrum left side dividing value Leftr,Leftg, Leftb and the right dividing value Rightr, Rightg, Rightb, get Leftr, Leftg, LeftbIn maximum be set as Left, get minimum of a value in Rightr, Rightg, Rightb and be set as Right;

(2) determine transformation parameter Theta and the Delta that Zadeh-X converts:

Theta＝Left；

Delta＝Right-Left；

(3) the red, green, blue three-component of source images S is carried out respectively to Zadeh-X conversion, generate conversionAfter digital picture be standardized images B;

Described Zadeh-X transform method is as follows:

$T(k,x,y)=k\frac{O(x,y)-Theta}{Delta}$

Constraints is:

$T(k,x,y)=\left\{\begin{array}{cc}k,& T(k,x,y)>k\\ 0,& T(k,x,y)<0\end{array}\right.$

In above formula, O (x, y) represents the colourity of three kinds of components of red, green, blue of source images S pixel (x, y)Value; Three kinds of components of red, green, blue of the rear standardized images B pixel (x, y) of T (k, x, y) expression conversionChromatic value; K=255.

Standardized images B is for source images S, and brightness and contrast is improved, from peopleThe visual effect of eye, quality is improved.

Step 3: standardized images B is carried out to quick optimization, obtain optimization image Z;

Optimization converts realization by Zadeh-X fast, in Zadeh-X conversion, and two transformation parametersDelta1 and Theta1 respectively value are:

Delta1＝5×AL^0.811

Theta1＝0

Be that Zadeh-X conversion can be exchanged into:

Constraints is: $T1(k,x,y)=\left\{\begin{array}{cc}k,& T1(k,x,y)>k\\ 0,& T1(k,x,y)<0\end{array}\right.$

In above formula, O1 (x, y) represents three kinds of components of red, green, blue of standardized images B pixel (x, y)Chromatic value; T1 (k, x, y) represents the red, green, blue three of the rear optimization image Z pixel (x, y) of conversionPlant the chromatic value of component; K=255; AL is the mean flow rate of source images S.

The Delta that the present invention chooses in the quick optimization procedures of step 3 is numeral under research low-light (level)After the feature of image, obtain through a large amount of Test Summaries, in actual applications, do not need manually to sweepRetouch, just can the adaptive optimization that realizes picture quality. The optimized adaptive transformation of picture quality alsoKey of the present invention, adaptive basis is the mean flow rate of original image, and mean flow rate is imageSpecial.

The three-component chromatic value of red, green, blue of gray level image is all identical, three kinds of components that obtainColourity spectrum is also identical, and we can think that it is a kind of special coloured image. Gray level image brightDegree is gray scale. In standardisation process, can adopt above-mentioned standardized transformation method to this gray level imageGray value convert, that is, first obtain Gray Spectrum, then the left side dividing value Left of Gray Spectrum is composedValue is to Theta, poor by Gray Spectrum the right dividing value Right and left side dividing value Left, i.e. and Right-Left,Assignment, to Delta, then converts by Zadeh-X, just can obtain the standardized images of gray level image.In optimization procedures, directly the gray scale of standardization gray level image is carried out to Zadeh-X conversion, just canRealize the best in qualityization of gray level image.

Remarkable result of the present invention is: utilize Zadeh-X transform method, and through two main steps,Be standardization and quick optimization, just can obtain the optimization image of low-light (level) digital picture. The present inventionDo not need through Multiple-Scan, just can realize adaptively low-light (level) number according to the mean flow rate of original imageThe optimization of word image, has saved the processing time greatly, realizes the optimized reality of digital picture qualityIn time, processes, and is effectively applied to field of video processing.

Brief description of the drawings

Fig. 1 flow chart of the present invention;

Fig. 2 (a) is the source images in embodiment 1, and Fig. 2 (b) is the optimization image of Fig. 2 (a);

Fig. 3 (a) is the source images in embodiment 2, and Fig. 3 (b) is the optimization image of Fig. 3 (a);

Fig. 4 (a) is the source images in embodiment 3, and Fig. 4 (b) is the optimization image of Fig. 4 (a).

Detailed description of the invention

Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail.

Embodiment 1:

Flow process as shown in Figure 1: the quick self-adapted optimization method of digital picture under a kind of low-light (level), bagDraw together the following step:

Step 1: selecting the digital picture Fig. 2 (a) obtaining under low-light (level) is source images S, obtains source imagesChromatic value R (x, y), G (x, y), the B (x, y) of three kinds of components of red, green, blue of the each pixel of S, pressAccording to Chinese patent " for the high-resolution detection method of the gradation of image/chrominance information of bottom layer image mining " (speciallyProfit number: the method 200610054324.9), make the colourity of three kinds of components of red, green, blue and compose, andCalculate the brightness value L (x, y) of each pixel, obtain the mean flow rate AL=6.7573 of source images S;

Step 2: generate the standardized images B of source images S, standardized images B obtains by the following method:

(1) search for respectively three kinds of component colourities of source images S red, green, blue spectrum left side dividing value Leftr,Leftg, Leftb and the right dividing value Rightr, Rightg, Rightb, get Leftr, Leftg, LeftbIn maximum be set as Left, get minimum of a value in Rightr, Rightg, Rightb and be set as Right;

(2) determine transformation parameter Theta and the Delta that Zadeh-X converts:

Theta＝Left；

Delta＝Right-Left；

(3) the red, green, blue three-component of source images S is carried out respectively to Zadeh-X conversion, generate conversionAfter digital picture be standardized images B;

Described Zadeh-X transform method is as follows:

$T(k,x,y)=k\frac{O(x,y)-Theta}{Delta}$

Constraints is:

$T(k,x,y)=\left\{\begin{array}{cc}k,& T(k,x,y)>k\\ 0,& T(k,x,y)<0\end{array}\right.$

In above formula, O (x, y) represents the colourity of three kinds of components of red, green, blue of source images S pixel (x, y)Value; Three kinds of components of red, green, blue of the rear standardized images B pixel (x, y) of T (k, x, y) expression conversionChromatic value; K=255.

Step 3: standardized images B is carried out to quick optimization, obtain the optimization shown in Fig. 2 (b)Image Z;

Optimization converts realization by Zadeh-X fast, in Zadeh-X conversion, and two transformation parametersDelta1 and Theta1 respectively value are:

Delta1＝5×AL^0.811

Theta1＝0

Be that Zadeh-X conversion can be exchanged into:

Constraints is: $T1(k,x,y)=\left\{\begin{array}{cc}k,& T1(k,x,y)>k\\ 0,& T1(k,x,y)<0\end{array}\right.$

In above formula, O1 (x, y) represents three kinds of components of red, green, blue of standardized images B pixel (x, y)Chromatic value; T1 (k, x, y) represents the red, green, blue three of the rear optimization image Z pixel (x, y) of conversionPlant the chromatic value of component; K=255; AL is the mean flow rate of source images S.

The mean flow rate of the optimization image shown in Fig. 2 (b) is 109.6411, compares the flat of Fig. 2 (a)All brightness 6.7573, the mean flow rate of Fig. 2 (b) is improved, from the visual effect of human eye,Picture quality is better.

Embodiment 2:

The present embodiment and embodiment 1 are roughly the same, and its difference is: the source images S of the present embodimentAs shown in Fig. 3 (a), the mean flow rate calculating is 47.2394; The optimization image finally obtaining asShown in Fig. 3 (b), mean flow rate is 106.4164, and optimization image is compared with source images, mean flow rateBe improved, from people's visual effect, quality is also better.

Embodiment 3:

The source images S that the present embodiment adopts, as shown in Fig. 4 (a), is a width gray level image, and it is quickThe optimized process of self adaptation as shown in Figure 1, comprises the following steps:

Step 1: selecting the digital picture Fig. 4 (a) obtaining under low-light (level) is source images S, because gray-scale mapChromatic value R (x, y), G (x, y), the B (x, y) of three kinds of components of red, green, blue of picture are identical, according toChinese patent " for the high-resolution detection method of the gradation of image/chrominance information of bottom layer image mining " (speciallyProfit number: the method 200610054324.9), make the Gray Spectrum of this image, and calculate each pixelThe brightness value L (x, y) of point, obtains the mean flow rate AL=8.8283 of source images S;

Step 2: generate the standardized images B of source images S, standardized images B obtains by the following method:

(1) left side dividing value of searching for respectively source images S Gray Spectrum is set as Left, the right margin of Gray SpectrumValue is set as Right;

(2) determine transformation parameter Theta and the Delta that Zadeh-X converts:

Theta＝Left；

Delta＝Right-Left；

(3) Zadeh-X conversion is carried out in the brightness to the each pixel of source images S (being gray scale), generatesDigital picture after conversion is standardized images B;

Described Zadeh-X transform method is as follows:

$T(k,x,y)=k\frac{O(x,y)-Theta}{Delta}$

Constraints is:

$T(k,x,y)=\left\{\begin{array}{cc}k,& T(k,x,y)>k\\ 0,& T(k,x,y)<0\end{array}\right.$

In above formula, O (x, y) represents the brightness value of source images S pixel (x, y); T (k, x, y) represents conversionThe brightness value of rear standardized images B pixel (x, y); K=255.

Step 3: standardized images B is carried out to quick optimization, obtain the optimization shown in Fig. 4 (b)Image Z;

Optimization converts realization by Zadeh-X fast, in Zadeh-X conversion, and two transformation parametersDelta1 and Theta1 respectively value are:

Delta1＝5×AL^0.811

Theta1＝0

Be that Zadeh-X conversion can be exchanged into:

Constraints is: $T1(k,x,y)=\left\{\begin{array}{cc}k,& T1(k,x,y)>k\\ 0,& T1(k,x,y)<0\end{array}\right.$

In above formula, O1 (x, y) represents the brightness value of standardized images B pixel (x, y); T1 (k, x, y) tableShow the brightness value of the rear optimization image Z pixel (x, y) of conversion; K=255; AL is the average of source images SBrightness.

The mean flow rate of the optimization image shown in Fig. 4 (b) is 100.0388, compares the flat of Fig. 4 (a)All brightness 8.8283, the mean flow rate of Fig. 4 (b) is improved, from the visual effect of human eye,Picture quality is better.

Claims (1)

1. the quick self-adapted optimization method of digital picture under low-light (level), is characterized in that comprising following stepRapid:

Step 1: selecting the digital picture obtaining under low-light (level) is source images S, obtains the each picture of source images SChromatic value R (x, y), G (x, y), the B (x, y) of three kinds of components of red, green, blue of vegetarian refreshments, make red, green,The colourity of blue three kinds of components is composed, and calculates the brightness value L (x, y) of each pixel, obtains source images S'sMean flow rate AL;

Step 2: generate the standardized images B of source images S, standardized images B obtains by the following method:

(1) search for respectively three kinds of component colourities of source images S red, green, blue spectrum left side dividing value Leftr,Leftg, Leftb and the right dividing value Rightr, Rightg, Rightb, get Leftr, Leftg, LeftbIn maximum be set as Left, get minimum of a value in Rightr, Rightg, Rightb and be set as Right;

(2) determine transformation parameter Theta and the Delta that Zadeh-X converts:

Theta＝Left；

Delta＝Right-Left：

(3) the red, green, blue three-component of source images S is carried out respectively to Zadeh-X conversion, generate conversionAfter digital picture be standardized images B;

Described Zadeh-X transform method is as follows:

$T(k,x,y)=k\frac{O(x,y)-Theta}{Delta}$

Constraints is:

$T(k,x,y)=\left\{\begin{array}{cc}k,& T(k,x,y)>k\\ 0,& T(k,x,y)<0\end{array}\right.$

In above formula, O (x, y) represents the colourity of three kinds of components of red, green, blue of source images S pixel (x, y)Value; Three kinds of components of red, green, blue of the rear standardized images B pixel (x, y) of T (k, x, y) expression conversionChromatic value; K=255;

Step 3: standardized images B is carried out to quick optimization, obtain optimization image Z;

Optimization converts realization by Zadeh-X fast, in Zadeh-X conversion, and two transformation parametersDelta1 and Theta1 respectively value are:

Delta1＝5×AL^0.811

Theta1＝0

Be that Zadeh-X conversion can be exchanged into: $T1(k,x,y)=k\frac{O1(x,y)-0}{5\&times;{\mathrm{AL}}^{0.811}}$

Constraints is: $T1(k,x,y)=\left\{\begin{array}{cc}k,& T1(k,x,y)>k\\ 0,& T1(k,x,y)<0\end{array}\right.$

In above formula, O1 (x, y) represents three kinds of components of red, green, blue of standardized images B pixel (x, y)Chromatic value; T1 (k, x, y) represents the red, green, blue three of the rear optimization image Z pixel (x, y) of conversionPlant the chromatic value of component; K=255; AL is the mean flow rate of source images S.