CN101345891B - Non-reference picture quality appraisement method based on information entropy and contrast - Google Patents

Abstract

The invention discloses a non-reference image quality evaluation method based on information entropy and contrast, comprising the following steps: 1, obtaining an original image; 2, transforming the original image into a gray level image; 3, computing average gray level of the original image and continuous bandwidth of the gray spectrum; 4, determining the search range of the gray initial value Theta and the gray level Delta; 5, performing Zadeh-X transformation to the image according to Theta and Delta values; 6, computing average contrast and information entropy of the transformed image, constructing a non-reference image quality evaluation function by the product of the average contrast and the information entropy, and computing the value thereof; 7, adding 1 to Delta and returning to step 5; 8, computing the maximum of the evaluation function after finishing research as well as corresponding delta and Theta values, performing Zadeh-X transformation to the original image according to the two values and then obtaining the best quality image. The invention provides the criterion of the best image quality, and obtains the best quality image according to the criterion.

Description

Non-reference picture quality appraisement method based on comentropy and contrast

Technical field

The present invention relates to image processing field, specifically, is that a kind of decline type gray scale that has from 0 gray scale that is used to estimate based on comentropy and contrast is composed the non-reference picture method for quality that distributes.

Background technology

The objective evaluation of picture quality is an important very difficult again problem during computer digital image is handled, current a large amount of research and patents all is about the reference picture quality evaluation is arranged, estimate the situation that degrades of image after treatment, non-reference picture quality appraisement (NR-IQA:no reference image quality assessment) then is the most important and the most difficult task that computer digital image is handled, and it has the application of following three aspects: (1) is used for image/video supervisory control system monitoring image quality; (2) be used to adjust image/video treatment system and algorithm; (3) be used for embedded images/processing system for video with optimized algorithm and parameter setting.But present non-reference picture quality appraisement technology is to estimate the improvement of quality behind the image denoising, does not relate to the criterion of optimum picture quality.

Summary of the invention

The object of the present invention is to provide a kind of non-reference picture quality appraisement method, the criterion that obtains optimum picture quality is provided based on comentropy and contrast.

To achieve these goals, technical scheme of the present invention is as follows: a kind of non-reference picture quality appraisement method based on comentropy and contrast, and its key is to carry out as follows:

(1) obtains original image;

Original image is a digital picture, can pass through acquisitions such as camera, video camera, monitor.

(2) original image is converted to original-gray image;

If original image originally as gray level image, does not then need conversion, if original image then needs to be converted into gray level image originally as coloured image, coloured image is converted to gray level image two kinds of methods:

First kind is to adopt normalization weighted sum formula that coloured image is converted to gray level image:

O(x，y)＝R(x，y)×0.3+G(x，y)×0.59+B(x，y)×0.11

In the formula, R (x, y), G (x, y), (x y) is respectively pixel (x, three kinds of chromatic values of red, green, blue y) to B.(x is y) for changing the gray value of back corresponding points for O.

Second kind is that power conversion formulas such as employing are changed:

O(x，y)＝R(x，y)/3+G(x，y)/3+B(x，y)/3

In the formula, R (x, y), G (x, y), (x y) is respectively pixel (x, three kinds of chromatic values of red, green, blue y) to B.(x is y) for changing the gray value of back corresponding points for O.

(3) (x, y) information are calculated the average gray value of this original-gray image to obtain the gray value O of this original-gray image

With the gray scale spectrum, and according to this gray scale spectrum acquisition gray scale spectrum continuous bandwidth BW;

Described gray scale spectrum continuous bandwidth is represented one section tonal range of spectral line continuous distribution, begin search from first spectral line of gray scale spectrum, in case do not have spectral line on certain gray scale, promptly no pixel exists on this gray scale, then stop search, the width of this section Continuous Gray Scale spectrum is bandwidth BW.

Described gray scale spectrum is pressed following formula and is obtained:

$T\left(g\right)=\frac{O^{1/m}\left(g\right)}{\underset{g=0}{\overset{255}{\mathrm{\Σ}}}{O}^{1/m}\left(g\right)}\underset{g=0}{\overset{255}{\mathrm{\Σ}}}O\left(g\right)$

In the formula, m is the planarization level, get [1, the ∞) integer between.Correlation theory is seen the Chinese invention patent (patent No.: ZL200610054324.9) that " is used for the gradation of image of bottom layer image mining or the high-resolution detection method of chrominance information ".

(4) determine gray scale initial value Theta and hunting zone; And give tonal range Delta with the starting point assignment of hunting zone;

(5) according to the gray value O of described gray scale initial value Theta, tonal range Delta and original-gray image (x y), carries out conversion with the Zadeh-X transform method to original-gray image, obtain after one group of conversion the T of grey scale pixel value as a result (x, y);

Described Zadeh-X transform method adopts following formula to calculate:

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

Wherein, (x y) is the coordinate of each pixel in the image, O (x, y) scope is [0,255], and T (x, scope y) is [0,255], Theta is an integer, and span is [0,255], Delta is a positive integer, and span is [1,255], K represents contraction-expansion factor, and span is [1,255], be more evenly distributed, generally get K=255 in order to make the gradation of image after the conversion.

When O (x, y)＜during Theta, T (x, y)=0; When O (x, in the time of y)＞(Theta+Delta), T (x, y)=255.Correlation theory see Chinese invention patent " bottom layer image hide and method for digging and adopt the image concealing and the excavating gear of this method " (the patent No.: ZL200610054379.X).

(6) (x y), calculates this average contrast of grey scale pixel value correspondence as a result according to the T of grey scale pixel value as a result after the conversion that obtains With comentropy InEn;

(7) according to the average contrast

With comentropy InEn, obtain the value IQAF of evaluation function, described evaluation function is:

$\mathrm{IQAF}=\stackrel{\‾}{C}\×\mathrm{InEn}$

(8) Delta is added 1, turn back to step (five) again, terminal point up to the hunting zone;

(9) after search finishes, find out the maximum IQAF and the Delta value of this IQAF correspondence, original-gray image is carried out conversion, obtain the T of the grey scale pixel value as a result (x after one group of conversion with the Zadeh-X transform method, y), the image of this value formation is best quality image.

In other words, the criterion of optimum picture quality is the maximum of IQAF, the Delta value corresponding according to maximum IQAF value, and (x y), just can obtain the image of best in quality with the Zadeh-X transform method in conjunction with the gray value O of Theta and original image again.

In described step (four), described gray scale initial value Theta is the gray scale spectrum starting point gray value of band continuously, and the starting point of hunting zone is the average gray value of original-gray image

Terminal point is

The present invention is used to assess the image that has from the decline type gray scale spectrum distribution of 0 gray scale, so Theta generally gets 0 value.And find that in actual search maximum generally exists

The preceding appearance is so the terminal point of hunting zone is made as

Can save search time.

The average gray value of described gray level image Obtain by following formula:

$\stackrel{\‾}{G}=\frac{1}{M\×N}\stackrel{N-1}{\mathrm{\Σ}}\stackrel{M-1}{\mathrm{\Σ}}\mathrm{Gray}(x,y)$

In the formula, (x is that (M, N are the pixel count of x, y direction to pixel for x, gray scale y) y) to Gray.Because Delta is a positive integer, if therefore calculate average gray value

With

Be decimal, then adopt the mode round up, they are adjusted into integer after assignment give Delta.

In described step (six), described average contrast Obtain by following formula:

$\stackrel{\‾}{C}=\frac{1}{(M-1)\×(N-1)}\stackrel{N-2}{\mathrm{\Σ}}\stackrel{M-2}{\mathrm{\Σ}}|\mathrm{Gray}(x,y)-\mathrm{Gray}(x+1,y)|$

In the formula, (x is that (M, N are the pixel count of x, y direction to pixel for x, gray scale y) y) to Gray.

In described step (six), described comentropy InEn is obtained by following formula:

$\mathrm{InEn}=-\stackrel{255}{\mathrm{\Σ}}p\left(i\right){\mathrm{Log}}_{2}p\left(i\right)$

In the formula, the probability of the pixel of p (i) expression gray scale i.

Beneficial effect: the present invention proposes a kind of non-reference picture quality appraisement method based on comentropy and contrast, be used to estimate and have the image that distributes from the decline type gray scale spectrum of 0 gray scale, adopting the product of comentropy and contrast is evaluation function, and search for this evaluation function maximum, the image of the corresponding best in quality of this maximum, the criterion of optimum picture quality is provided,, has obtained the image of best in quality according to this evaluation function maximum corresponding parameters.

Description of drawings

Fig. 1 is a workflow schematic diagram of the present invention;

Fig. 2 is an original image;

Fig. 3 is the picture quality comparison diagram, a) is original image shown in Figure 2 wherein, b) is the image of IQAF maximum correspondence, c) is the corresponding image of another IQAF value.

Embodiment

Further the present invention is illustrated below in conjunction with drawings and Examples.

As shown in Figure 1: a kind of non-reference picture quality appraisement method based on comentropy and contrast, carry out as follows:

(1) obtains original image;

Original image is a digital picture, can pass through acquisitions such as camera, video camera, monitor.As shown in Figure 2: the width of cloth gray scale pictures of original image under low lighting condition, taking.

(2) original image is converted to original-gray image;

As shown in Figure 2, original image does not need to change originally as gray level image.If but original image is a coloured image, then needs to be converted into gray level image, coloured image is converted to gray level image two kinds of methods:

First kind is to adopt normalization weighted sum formula to change:

O(x，y)＝R(x，y)×0.3+G(x，y)×0.59+B(x，y)×0.11

In the formula, R (x, y), G (x, y), (x y) is respectively pixel (x, three kinds of chromatic values of red, green, blue y) to B.(x is y) for changing the gray value of back corresponding points for O.

Second kind is that power conversion formulas such as employing are changed:

O(x，y)＝R(x，y)/3+G(x，y)/3+B(x，y)/3

In the formula, R (x, y), G (x, y), (x y) is respectively pixel (x, three kinds of chromatic values of red, green, blue y) to B.(x is y) for changing the gray value of back corresponding points for O.

(3) (x, y) information are calculated the average gray value of this original-gray image to obtain the gray value O of this original-gray image With the gray scale spectrum, and according to this gray scale spectrum acquisition gray scale spectrum continuous bandwidth BW;

The average gray value of described gray level image Obtain by following formula:

$\stackrel{\‾}{G}=\frac{1}{M\×N}\stackrel{N-1}{\mathrm{\Σ}}\stackrel{M-1}{\mathrm{\Σ}}\mathrm{Gray}(x,y)$

In the formula, (x is that (M, N are the pixel count of x, y direction to pixel for x, gray scale y) y) to Gray.The average gray value of image shown in Fig. 2

Being 4.7758, is 5 after rounding up.

Described gray scale spectrum continuous bandwidth is represented one section tonal range of spectral line continuous distribution, begin search from first spectral line of gray scale spectrum, in case do not have spectral line on certain gray scale, promptly no pixel exists on this gray scale, then stop search, the width of this section Continuous Gray Scale is bandwidth BW.

Described gray scale spectrum is pressed following formula and is obtained:

$T\left(g\right)=\frac{O^{1/m}\left(g\right)}{\underset{g=0}{\overset{255}{\mathrm{\Σ}}}{O}^{1/m}\left(g\right)}\underset{g=0}{\overset{255}{\mathrm{\Σ}}}O\left(g\right)$

In the formula, m is the planarization level, get [1, the ∞) integer between.Correlation theory is seen the Chinese invention patent (patent No.: ZL200610054324.9) that " is used for the gradation of image of bottom layer image mining or the high-resolution detection method of chrominance information ".These gray scale spectrum computational methods have the precision of a pixel, calculate the continuous bandwidth BW=66 of gradation of image spectrum among Fig. 2 according to following formula.

(4) determine the hunting zone of gray scale initial value Theta and Delta; Described gray scale initial value Theta is the gray scale spectrum starting point gray value of band continuously, and the starting point of Delta hunting zone is the average gray value of original-gray image

Terminal point is

The present invention is used to estimate the image that has from the decline type gray scale spectrum distribution of 0 gray scale, so Theta generally gets 0 value.And find that in actual search maximum generally exists

The preceding appearance is so the terminal point of hunting zone is made as

Can save search time.

In the present embodiment, the starting point of hunting zone is 5, and terminal point is 13.

(5) according to the gray value O of described gray scale initial value Theta, tonal range Delta and original-gray image (x y), carries out conversion with the Zadeh-X transform method to original-gray image, obtain after one group of conversion the T of grey scale pixel value as a result (x, y);

Described Zadeh-X transform method adopts following formula to calculate:

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

Wherein, (x y) is the coordinate of each pixel in the image, O (x, scope y) is [0,255], T (x, scope y) is [0,255], Theta ∈ [0,255], Delta ∈ [1,255], K represents contraction-expansion factor, span be [, 255], be more evenly distributed, generally get K=255 in order to make the gradation of image after the conversion.

When O (x, y)＜during Theta, T (x, y)=0; When O (x, in the time of y)＞(Theta+Delta), T (x, y)=255.

(6) (x y), calculates this average contrast of grey scale pixel value correspondence as a result according to the T of grey scale pixel value as a result after the conversion that obtains

With comentropy InEn;

Described average contrast

Obtain by following formula:

$\stackrel{\‾}{C}=\frac{1}{(M-1)\×(N-1)}\stackrel{N-2}{\mathrm{\Σ}}\stackrel{M-2}{\mathrm{\Σ}}|\mathrm{Gray}(x,y)-\mathrm{Gray}(x+1,y)|$

In the formula, (x is that (M, N are the pixel count of x, y direction to pixel for x, gray scale y) y) to Gray.

Described comentropy InEn is obtained by following formula:

$\mathrm{InEn}=-\stackrel{255}{\mathrm{\Σ}}p\left(i\right){\mathrm{Log}}_{2}p\left(i\right)$

(7) according to the average contrast With comentropy InEn, obtain the value IQAF of evaluation function, described evaluation function is:

$\mathrm{IQAF}=\stackrel{\‾}{C}\×\mathrm{InEn}$

(8) tonal range Delta is added 1, turn back to step (five) again, terminal point up to the hunting zone;

(9) searched for after, find out the maximum IQAF and the Delta value of this IQAF correspondence, with the Zadeh-X transform method original-gray image is carried out conversion, obtain the T of the grey scale pixel value as a result (x after one group of conversion, y), (x, y) image of Gou Chenging is best quality image to this grey scale pixel value T.

Following table has shown the hunting zone according to delta, searches for the evaluation function value that obtains one by one:

As shown in Figure 3: among the figure, a) be original image shown in Figure 2, the image of correspondence when b) being Delta=8, the image of correspondence when c) being Delta=2 for the IQAF maximum.We as can be seen, picture quality the best of IQAF maximum correspondence, and the average gray value of this figure

Near 128.

Claims (5)

1. a kind of no reference image quality evaluation method based on information entropy and contrast, it is characterized in that carry out as follows: (1) Obtain the original image; (2) converting the original image into an original grayscale image; (3) Obtain the grayscale value O(x, y) information of the original grayscale image, and calculate the average grayscale value of the original grayscale image

and the gray spectrum, and obtain the continuous bandwidth BW of the gray spectrum according to the gray spectrum; (4) Determine the search range of grayscale starting value Theta and grayscale level Delta; (5) According to the grayscale initial value Theta, the grayscale level Delta and the grayscale value O(x, y) of the original grayscale image, the original grayscale image is transformed with the Zadeh-X transformation method to obtain a set of The transformed result pixel gray value T(x, y); (6) According to the obtained converted result pixel gray value T(x, y), calculate the average contrast corresponding to the result pixel gray value

and information entropy InEn; (7) According to the average contrast

And information entropy InEn, obtain the value IQAF of evaluation function, described evaluation function is: $\mathrm{<span\; class="notranslate">\; IQAF</span>}<span\; class="notranslate">\; =</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; InEn</span>}$ (8) add 1 to the gray level Delta, and then return to step (5), until the end of the search; (9) After the search is completed, find the largest IQAF and the Delta value corresponding to the IQAF, use the Zadeh-X transformation method to transform the original grayscale image, and obtain a set of transformed result pixel grayscale values T(x, y ), the image formed by the resulting pixel gray value T(x, y) is the best quality image. 2. the no-reference image quality evaluation method based on information entropy and contrast according to claim 1, is characterized in that: in described step (4), described gray scale starting value Theta is the starting point of gray spectrum continuous band Gray value, the starting point of the gray level Delta search range is the average gray value of the original gray image

end point is

3. The no-reference image quality evaluation method based on information entropy and contrast according to claim 2, characterized in that: the average gray value of the grayscale image

Obtained by the following formula: $\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; G</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; N</span>}}\stackrel{\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\stackrel{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\mathrm{<span\; class="notranslate">\; Gray</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>$ In the formula, Gray(x, y) is the gray level of the pixel point (x, y), and M and N are the number of pixels in the x and y directions. 4. the no-reference image quality evaluation method based on information entropy and contrast according to claim 1, is characterized in that: in described step (6), described average contrast

Obtained by the following formula: $\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>}\stackrel{\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\stackrel{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}<span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; Gray</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Gray</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; |</span>$ In the formula, Gray(x, y) is the gray level of the pixel point (x, y), and M and N are the number of pixels in the x and y directions. 5. the no-reference image quality evaluation method based on information entropy and contrast according to claim 1, is characterized in that: in described step (6), described information entropy InEn is obtained by following formula: $\mathrm{<span\; class="notranslate">\; InEn</span>}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; -</span>\stackrel{\mathrm{<span\; class="notranslate">\; 255</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; log</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>$ In the formula, p(i) represents the probability of the pixel whose gray level is i in the gray spectrum.

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