title: Quality Index for Stereoscopic Images by Separately Evaluating Adding and Subtracting.
abstract: The human visual system (HVS) plays an important role in stereo image quality perception. Therefore, it has aroused many people's interest in how to take advantage of the knowledge of the visual perception in image quality assessment models. This paper proposes a full-reference metric for quality assessment of stereoscopic images based on the binocular difference channel and binocular summation channel. For a stereo pair, the binocular summation map and binocular difference map are computed first by adding and subtracting the left image and right image. Then the binocular summation is decoupled into two parts, namely additive impairments and detail losses. The quality of binocular summation is obtained as the adaptive combination of the quality of detail losses and additive impairments. The quality of binocular summation is computed by using the Contrast Sensitivity Function (CSF) and weighted multi-scale (MS-SSIM). Finally, the quality of binocular summation and binocular difference is integrated into an overall quality index. The experimental results indicate that compared with existing metrics, the proposed metric is highly consistent with the subjective quality assessment and is a robust measure. The result have also indirectly proved hypothesis of the existence of binocular summation and binocular difference channels.
authors.affiliation: School of Electronic Information Engineering, Tianjin University, 92 Weijin Road, Tianjin, 300072 China.
authors.forename: Jiachen
authors.initials: J
authors.lastname: Yang
authors.affiliation: School of Electronic Information Engineering, Tianjin University, 92 Weijin Road, Tianjin, 300072 China.
authors.forename: Yancong
authors.initials: Y
authors.lastname: Lin
authors.affiliation: School of Electronic Information Engineering, Tianjin University, 92 Weijin Road, Tianjin, 300072 China.
authors.forename: Zhiqun
authors.initials: Z
authors.lastname: Gao
authors.affiliation: Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen, 518055 China.
authors.forename: Zhihan
authors.initials: Z
authors.lastname: Lv
authors.affiliation: School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, Shaanxi 710048 China.
authors.forename: Wei
authors.initials: W
authors.lastname: Wei
authors.affiliation: Department of Electrical and Computer Engineering, West Virginia University, Montgomery, WV 25136 United States of America.
authors.forename: Houbing
authors.initials: H
authors.lastname: Song
mesh_terms: D015350:Contrast Sensitivity / Q000502:physiology; D019992:Databases as Topic; D003867:Depth Perception / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D010470:Perceptual Masking / Q000502:physiology; D015348:Vision, Binocular / Q000502:physiology