Method for objectively evaluating image quality based on region weight and visual characteristics of human eyes

Abstract

The invention discloses a method for objectively evaluating the image quality based on region weight and visual characteristics of human eyes, which comprises the following steps: (1) acquiring images which are distributed according to the region weight; (2) applying modified human eyes to process images of sensitive functions; and (3) applying gradient information similarity to evaluate the images. The method is combined with the visual characteristics of the human eyes, so that the image processing result of the method is quite close to a human eye visual system, and the quality evaluation value according with the visual characteristics of the human eyes can be obtained as long as a reference image and an evaluation image are inputted. The method can be applied in the aspects of image compression, storage, transmission, reconstruction and the like, and quickly measures the image quality. Moreover, the method can be applied to iteration ending in the image restoration process, and the optimum restoration image obtained by using an evaluation algorithm to end an iteration algorithm is quite close to the optimum restoration image obtained by the evaluation of the human eyes.

Description

technical field [0001] The invention relates to computer image processing technology, in particular to an objective evaluation method of image quality based on region weight and human visual characteristics. Background technique [0002] With the development of human society towards high digitization, the rapid development and popularization of digital image, digital video and digital TV will become inevitable. In the various technologies of digital image processing, digital images may be subject to various degradations and distortions during the process of acquisition, compression, storage, transmission and reconstruction, and image degradation will inevitably occur. How to evaluate them more effectively The problem of image quality also arises at the historic moment. The output image quality of an image transmission, processing or compression system ultimately determines the quality of its technology and system. Therefore, the practical significance of image quality evalu...

AI Technical Summary

Problems solved by technology

However, it simply measures the grayscale difference between images or the relationship between signal and noise, and lacks stability under different image degradation conditions.

[0008] The newer algorithm is the SSIM (Structural Similarity) algorithm proposed by Wang Zhou et al., but its ability to evaluate images with a slightly larger degree of blur, slightly larger noise, and slightly more ringing ripples is poor.

[0009] The previous methods were poor mainly because they did not consider the visual characteristics of the human eye, or did not notice people's selective observation of image content (different areas receive different degrees of attention)

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