No-reference three-dimensional image quality evaluation method based on fused image and reinforced image

Abstract

The non-reference three-dimensional image quality evaluation method based on the fused image and the enhanced image comprises the following steps: firstly, performing red, green and blue three-channel fusion on left and right viewpoints of the three-dimensional image based on binocular fusion, binocular competition, binocular inhibition and other characteristics of a human vision system to obtain a color fused image; secondly, obtaining a disparity map of the distorted stereo image pair by using a stereo matching algorithm, and weighting a gray-scale map of the color fusion image by using a gradient weight of the disparity map; thirdly, generating an enhanced image according to the fused image and the disparity map; thirdly, extracting natural statistical characteristics from the fused image and the enhanced image in a spatial domain, and extracting kurtosis and skewness characteristics from the disparity map; and finally, fusing the extracted features, and sending the fused features into support vector regression (SVR) to obtain the quality of the to-be-evaluated stereo image.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to research on objective evaluation of stereoscopic image quality, in particular to an objective evaluation method of stereoscopic image quality without reference based on fused images and enhanced images. Background technique [0002] With the rapid development of 3D technology, stereoscopic image quality evaluation has become one of the indispensable research directions in the 3D field. At present, the evaluation methods of stereoscopic image quality can be divided into subjective evaluation and objective evaluation. Subjective evaluation conforms to the characteristics of human vision, but the implementation process is cumbersome, time-consuming and labor-intensive. operability, so a large number of scholars have devoted themselves to the field of objective evaluation [1-3] . [0003] According to the degree of using the original image information, the objective quality evaluation...

AI Technical Summary

Problems solved by technology

Shen [11] Considering the importance of spatial frequency to the human eye, the left and right views are processed with Gabor filters, and the processed left and right views are added to form a fusion image. This model can only conform to the human visual characteristics to a certain extent.

Images