No-reference quality evaluation method of compression perception recovery images

A technology for image restoration and compressed sensing, applied in image enhancement, image analysis, image data processing, etc., and can solve problems such as poor performance

Inactive Publication Date: 2017-02-22
CHINA UNIV OF MINING & TECH
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Problems solved by technology

Existing general methods perform poorly on these three parameters, with mediocre results on consistency and monotonicity between subjective scores

Method used

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  • No-reference quality evaluation method of compression perception recovery images
  • No-reference quality evaluation method of compression perception recovery images
  • No-reference quality evaluation method of compression perception recovery images

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Embodiment Construction

[0021] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0022] Such as figure 2 and image 3 as shown, image 3 There is obvious distortion. According to the distortion characteristics in the image, the features of the image are extracted. Furthermore, a model is trained with SVR through a collection of features. Through this model, the quality score of the image is predicted.

[0023] Such as figure 1 As shown, Step 1: The experiment is carried out in the 'compressed sensing restored image database'. A total of 300 images (512*512) in the database are restored images obtained by 10 compressed sensing restoration algorithms and 3 different compression degrees. They contain distortions of different kinds and degrees. Using the fuzzy evaluation algorithm LPC-SI, calculate the sharpness feature value X=(x ij ) M*N . Taking the average value of all elements in the sharpness feature value, that is Where i = 1, 2...

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Abstract

The present invention relates to a no-reference quality evaluation method of compression perception recovery images. The method comprises the steps of aiming at the distortion characteristics of the compression perception recovery images, extracting three local characteristics and five global characteristics of the images to evaluate the quality of the image, wherein the local characteristics comprise the image definition, the contrast and the homogeneity, and the global characteristics comprise four characteristics about the naturality of the images extracted by utilizing a generalized Gaussian model to fit the MSCN coefficients and one characteristic obtained by utilizing the singular value decomposition; and finally utilizing a support vector machine to train the above 8 characteristics to obtain a characteristic model, thereby applying the model to predict the quality scores of the images. The evaluation results of the method are better than the results of an international mainstream method, and have the very high consistency with the human eye subjective perception.

Description

technical field [0001] The invention relates to a no-reference quality evaluation method for image restoration by compressed sensing, and belongs to the field of image quality evaluation. Background technique [0002] Image quality evaluation can be divided into two methods: (1) subjective evaluation method: the observer evaluates the image quality; (2) objective evaluation method: uses algorithms to evaluate the image quality. Among them, the subjective evaluation method is consistent with people’s subjective feelings, but it is time-consuming and laborious, and cannot meet the actual application needs; the objective evaluation method has the characteristics of convenience and speed, and is easy to implement and can be combined into the application system, but it is often inconsistent with human subjective feelings. There are deviations. Generally speaking, the image quality evaluation refers to the objective evaluation algorithm, and its purpose is to obtain the objective...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T7/0002G06T2207/10016G06T2207/20081G06T2207/30168
Inventor 李雷达胡波周玉
Owner CHINA UNIV OF MINING & TECH
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