Eye exactly perceptible stereo image distortion analyzing method based on texture complexity

Abstract

The invention discloses an eye exactly perceptible stereo image distortion analyzing method based on texture complexity. From the point of the texture complexity, when an asymmetric stereo image is coded, the maximum quantization parameter coding range of the quality of a right viewpoint image capable of being reduced relative to the quality of a left viewpoint image is analyzed; through a large number of subjective tests, under a condition that the quality of the left viewpoint image is fixed, the critical value of the eye perceptible stereo image change quality of the right viewpoint is measured; the quantitative mathematic model relation among the maximum tolerable quantization parameter threshold value and the texture complexity of the right viewpoint image, and a coding quantization parameter is obtained through linear fitting; the coding compression efficiency can be improved through reducing the quality of the right viewpoint image; moreover, the reduction of the quality of the right viewpoint image cannot be sensed by an observer through a stereo vision masking effect; and therefore, the integral quality of the stereo image is ensured.

Description

technical field [0001] The present invention relates to a measurement and analysis technology for visual perception characteristics of stereoscopic images, in particular to a method for analyzing distortions of stereoscopic images that are just detectable by human eyes based on texture complexity, which is especially suitable for humans who encode asymmetrical stereoscopic images and video Eye Minimal Perceivable Distortion Analysis. Background technique [0002] Early psychological research found that there is a masking effect in human stereoscopic vision perception, that is, among the left and right viewpoint images that constitute a stereoscopic image, the viewpoint image with good quality contributes more to the overall stereoscopic image perception quality. Based on this psychological foundation, the researchers found through further research through subjective experiments that although the human eye has this stereoscopic masking effect when viewing a stereoscopic image...

AI Technical Summary

Problems solved by technology

The existing stereoscopic image distortion analysis method is a stereoscopic subjective perception experiment, mainly from the point of view that the quality of one viewpoint remains unchanged and the quality of the other viewpoint decreases as a whole, to measure the change of stereoscopic vision that the human eye can perceive, and only a right-hand view is obtained. Compared with the overall left-viewpoint image, the viewpoint image can just perceive the distortion threshold, while ignoring the influence of the texture complexity, brightness, color and other factors of different local regions of the stereo image on the local masking threshold of stereo vision

Obviously, for natural stereoscopic images with different textures and brightness distributions, if only one overall perceptual distortion threshold is used, it cannot reflect the local perceptual redundancy of the stereoscopic image well, and cannot maximize the compression of perceptual redundancy and improve coding compression. efficiency

Since the texture complexity is an important factor affecting the stereo masking effect, it is of great significance to study the influence of texture complexity on the stereo masking effect, and the quantitative research results on the influence of texture complexity on the stereo masking effect are rarely reported. Therefore, how to design a Analytical methods are necessary to quantify this critical value

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