Stereo image quality objective evaluation method

Abstract

The invention discloses a stereo image quality objective evaluation method, which comprises the following steps of: performing singular value decomposition on left and right viewpoint images of undistorted stereo images and distorted stereo images, extracting characteristic vectors of the left and right viewpoint images of the distorted stereo images, and performing linear weighting on the characteristic vectors of the left and right viewpoint images to obtain the characteristic vectors of the distorted stereo images; and training the characteristic vectors of the distorted stereo images of the same distortion type in a distorted stereo image set by using support vector regression, and testing each distorted stereo image of the same distortion type by utilizing a support vector regression training mode to obtain image quality objective evaluation predicted values of each distorted stereo image. The method has the advantages of mapping raw data into a high-dimensional characteristic space and performing linear estimation in the high-dimensional characteristic space to construct an optimal linear function so as to avoid the complex process of simulating the related characteristics and mechanism of a human vision system and improve correlation between objective evaluation results and subjective perception.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to an objective evaluation method for stereoscopic image quality. Background technique [0002] With the rapid development of image coding technology and stereoscopic display technology, stereoscopic image technology has received more and more attention and applications, and has become a current research hotspot. Stereoscopic image technology utilizes the binocular parallax principle of the human eye. Both eyes independently receive left and right viewpoint images from the same scene, and form binocular parallax through brain fusion, so as to enjoy a stereoscopic image with a sense of depth and realism. Due to the impact of acquisition system, storage compression and transmission equipment, stereoscopic images will inevitably introduce a series of distortions. Compared with single-channel images, stereoscopic images need to ensure the image quality of two channels at the same ti...

AI Technical Summary

Problems solved by technology

[0003] Stereo image quality objective evaluation methods can be mainly divided into two categories: 1) left and right channel image quality evaluation based on stereo perception, stereo perception evaluation is reflected by disparity or depth information, however, due to the limitations of current disparity/depth estimation technology, how to effectively Evaluating the quality of depth images or disparity images to truly characterize the stereoscopic perception characteristics

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