A full‐reference stereoscopic image quality assessment index based on stable aggregation of monocular and binocular visual features

Abstract

In stereoscopic image quality assessment, human visual system has been universally taken into account to detect perceptual characteristics. A novel full-reference stereoscopic image assessment metric by considering both monocular and binocular visual features of human visual system is proposed. In particular, a new region segmentation algorithm is firstly proposed to divide 3D images into occluded and non-occluded regions. The just noticeable difference model is employed on the occluded regions to formulate the monocular vision, while the binocular just noticeable difference model is applied to the non-occluded regions to reveal the binocular vision of the human visual system. In the proposed region segmentation, disparity information and Euclidean distance between stereo pairs are both adopted to solve the unstable segmentation problem of traditional methods. A new pooling strategy based on global edge features is then presented to aggregate the just noticeable difference and binocular just noticeable difference evaluation maps. In addition, some local image features as supplementary of just noticeable difference to describe visual characteristics of the human visual system are also extracted. Finally, an overall quality score is calculated based on the above-mentioned features to measure the visual quality of distorted stereo pairs. Experimental results show that the proposed metric achieves high consistency with the human visual system, and outperforms state-of-the-art algorithms on stereoscopic image quality assessment.

Stereoscopic Image Enabled Animation Art Design Exploration

“…The emergence of stereoscopic image technology shows people three-dimensional space; there is a real distance from the space, the real scene; the emergence of this technology is far more than two-dimensional to bring people the visual experience. With the development of this technology, as far as the eye can see from the network world to real life, virtual and real are not filled with traces of stereoscopic image technology; this new visual way is a two-dimensional plane to three-dimensional stereo magnificent metamorphosis [4][5][6].…”

A full reference quality assessment method with fused monocular and binocular features for stereo images

“… Chen & Zhao (2019) proposed a full reference method that combines local and global visual features to perceive the quality of stereoscopic images. Si et al (2021) first proposed a SIQA method to divide stereo images into occluded and non-occluded areas. First, the disparity information and the Euclidean distance between stereo pairs are used to find a segmentation strategy for occluded and non-occluded areas in the scene; the occluded areas represent monocular vision, and the unoccluded areas show binocular vision of HVS.…”