Stereo image quality objective evaluation method based on visual perception

Abstract

The invention discloses a stereo image quality objective evaluation method based on visual perception. Firstly, a stereo image is divided into a strong edge block, a weak edge block , a flat block and a texture block, and characteristic information reflecting image quality and depth perception of different zone blocks is extracted through computation so as to obtain stereo image characteristic vectors; and then the characteristic vectors of distorted stereo images of the same distortion type in a distorted stereo image set are trained through support vector regression, and each distorted stereo image of the same distortion type is tested by a support vector regression training model to obtain the objective image quality evaluation forecast value of each distorted stereo image. The method has the advantages that the obtained characteristic vector information reflecting the image quality and the depth perception has stronger stability and can better reflect the quality change condition of the stereo images, and the relevance of an objective evaluation result and subjective perception is improved.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to an objective evaluation method for stereoscopic image quality based on visual perception. 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 ...

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Problems solved by technology

[0003] The objective evaluation methods of stereoscopic image quality can be mainly divided into two categories: 1) Left and right channel image quality evaluation based on image quality, which directly applies the planar image quality evaluation method to evaluate the quality of stereoscopic images, but fuses the left and right viewpoint images of stereoscopic images The process of generating stereoscopic effect is still difficult to express with simple mathematical methods, and there is still mutual influence between left and right viewpoint images, and it is difficult to effect

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