Stereoscopic image quality assessment using disparity-compensated view filtering

Yang Song; Mei Yu; Gangyi Jiang; Feng Shao; Zongju Peng

doi:10.1117/1.JEI.25.2.023001

7 March 2016 Stereoscopic image quality assessment using disparity-compensated view filtering

Yang Song, Mei Yu, Gangyi Jiang, Feng Shao, Zongju Peng

Author Affiliations +

Funded by: Natural Science Foundation of China, National High-tech R&D Program of China

Journal of Electronic Imaging, Vol. 25, Issue 2, 023001 (March 2016). https://doi.org/10.1117/1.JEI.25.2.023001

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.

Citation Download Citation

Yang Song, Mei Yu, Gangyi Jiang, Feng Shao, and Zongju Peng "Stereoscopic image quality assessment using disparity-compensated view filtering," Journal of Electronic Imaging 25(2), 023001 (7 March 2016). https://doi.org/10.1117/1.JEI.25.2.023001

Published: 7 March 2016

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