Contrast distortion image quality evaluation method fusing image entropy and structural similarity characteristics

Abstract

The invention provides a contrast distortion image quality evaluation method fusing image entropy and structural similarity features, and belongs to the fields of image quality objective evaluation, image processing, machine vision and the like. According to the method, the image entropy and the structural similarity feature of the image are combined and fused, the defect that the image entropy feature is insensitive to the image structure is overcome, meanwhile, the structural feature and the entropy feature of the image are fused, and comprehensive quality evaluation is carried out on the image from the aspects of image pixel statistics and content structure; the problem of quantitative evaluation of image contrast distortion degradation in data processing processes of acquisition, transmission, conversion and the like is solved. According to the method, the evaluation process is not very complicated, the calculation efficiency is high, the accuracy is good, the image distortion can be well evaluated, and the evaluation data truly reflects the image degradation distortion degree and is consistent with the visual perception characteristics of human eyes; the method can meet the actual requirements of image quality distortion objective evaluation in the fields of image fusion, image enhancement, image recognition and the like.

Description

technical field [0001] The invention relates to the technical fields of objective evaluation of digital image quality, machine vision and artificial intelligence, and in particular to a contrast distortion image quality evaluation method that combines image entropy and structural similarity features. Background technique [0002] As we all know, digital images are inseparable from people's daily life, and their importance in people's work and life has become increasingly prominent. However, digital images are easily damaged in the process of collection and transmission, resulting in image distortion, resulting in insufficient aesthetics in display and essential loss of information content. Information is inconsistent. Therefore, in order to provide effective and real image processing data for image restoration, understanding, recognition and other applications, it is urgent to quantify and measure the distortion of the image. Image Quality Assessment (IQA) came into being a...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the technical defects that the existing image quality evaluation system lacks the objective evaluation of the degree of distortion degradation of contrast-distorted color images and the poor performance of the existing contrast-distorted image quality evaluation methods, and proposes a Contrast-Distorted Image Quality Evaluation Method by Fusion of Image Entropy and Structural Similarity Features

The present invention uses this method to solve the problem of objective evaluation of the image quality distortion and degradation caused by the image in the process of image transmission, storage, compression, editing, etc., and the obtained evaluation data can truly reflect the difference between the distorted and degraded image and the standard image. difference, and it is consistent with the visual perception of the human eye

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