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Journal of Electronic Imaging

Stereoscopic image quality assessment using disparity-compensated view filtering
Author(s): Yang Song; Mei Yu; Gangyi Jiang; Feng Shao; Zongju Peng
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Paper Abstract

Stereoscopic image quality assessment (IQA) plays a vital role in stereoscopic image/video processing systems. We propose a new quality assessment for stereoscopic image that uses disparity-compensated view filtering (DCVF). First, because a stereoscopic image is composed of different frequency components, DCVF is designed to decompose it into high-pass and low-pass components. Then, the qualities of different frequency components are acquired according to their phase congruency and coefficient distribution characteristics. Finally, support vector regression is utilized to establish a mapping model between the component qualities and subjective qualities, and stereoscopic image quality is calculated using this mapping model. Experiments on the LIVE 3-D IQA database and NBU 3-D IQA databases demonstrate that the proposed method can evaluate stereoscopic image quality accurately. Compared with several state-of-the-art quality assessment methods, the proposed method is more consistent with human perception.

Paper Details

Date Published: 7 March 2016
PDF: 7 pages
J. Electron. Imaging. 25(2) 023001 doi: 10.1117/1.JEI.25.2.023001
Published in: Journal of Electronic Imaging Volume 25, Issue 2
Show Author Affiliations
Yang Song, Ningbo Univ. (China)
Mei Yu, Ningbo Univ. (China)
Nanjing Univ. (China)
Gangyi Jiang, Ningbo Univ. (China)
Nanjing Univ. (China)
Feng Shao, Ningbo Univ. (China)
Zongju Peng, Ningbo Univ. (China)


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