Non-reference image quality evaluating method based on wavelet and structural self-similarity analysis

An image quality evaluation and self-similarity technology, applied in the field of image processing, can solve the problems of only considering the distribution characteristics, not reflecting, and not considering the factors of human eye adaptive adjustment

Inactive Publication Date: 2011-02-16
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

Although some new evaluation methods have emerged, most of them do not show superiority over MSE and PSNR methods.
[0003] Xie Zhengxiang, Liu Yuhong, and Hu Qin proposed a "no-reference image quality evaluation based on information entropy and contrast" in a Chinese invention patent application (application number 200810070170.1, application date 2008.8. Method", this method uses entr

Method used

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  • Non-reference image quality evaluating method based on wavelet and structural self-similarity analysis
  • Non-reference image quality evaluating method based on wavelet and structural self-similarity analysis
  • Non-reference image quality evaluating method based on wavelet and structural self-similarity analysis

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Embodiment Construction

[0021] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0022] as attached figure 1 For the original image shown in (a), when using the method of the present invention for quality evaluation, follow the steps below:

[0023] Step 1. Reconstruct the original image to be evaluated to include A new image of self-similar sub-blocks, It is an integer greater than or equal to 1; the specific method of said recombination is:

[0024] According to the following formula, the pixels in the original image I Moved to the new image I' in place,

[0025]

[0026] In the formula, L and H represent the width and height of the original image respectively, and mod is a modulo operation,

[0027] when , the new image I' is the recombined image containing A new image of self-similar sub-blocks, the recombination process is equivalent to using the similarity of the image in the spatial neighborhood, extracting ...

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Abstract

The invention discloses a non-reference image quality evaluating method based on wavelet and structural self-similarity analysis, which is used for image quality evaluation of grayscale images and belongs to the technical field of image processing. The method comprises the steps of: firstly, recombining an original image to be evaluated into a new image comprising 4<n>self-similarity sub-blocks; then, carrying out wavelet decomposition on the new image; computing a wavelet entropy; and finally evaluating quality according to a wavelet entropy value, wherein the smaller the wavelet entropy value is, the higher the quality of the images is and the better a visual effect is. Compared with other similar methods, in the method of the invention, a wavelet decomposition algorithm and the self-similarity of the images are combined for the first time; the entropy of a wavelet coefficient is computed for the first time; and a computing result (the wavelet entropy) is used for evaluating the quality of the images. Meanwhile, in the method, any reference image is not needed.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to a non-reference image quality evaluation method based on wavelet and structural self-similarity analysis, which is used for quality evaluation of grayscale images and belongs to the field of image processing. Background technique [0002] The objective evaluation of image quality is a very important and difficult problem in digital image processing. Most of the traditional image quality evaluation methods belong to the full-reference evaluation method. Including the common mean-squared error MSE algorithm, signal-to-noise ratio evaluation method (signal-to-noise ratio SNR), and peak signal-to-noise ratio evaluation method (peak signal-to-noise ratio PSNR). These evaluation methods are widely used in image compression, fusion, forensics and other fields [Martin Vetterli S Grace Chang, Bin Yu. "Adaptive wavelet sharing for image denoising and compression", IEEE Transaction on ...

Claims

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Application Information

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IPC IPC(8): H04N17/00
Inventor 焦峰姚勇雷马利薛胜军谢永华
Owner NANJING UNIV OF INFORMATION SCI & TECH
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