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Stereoscopic image quality assessment using disparity-compensated view filtering

[+] Author Affiliations
Yang Song, Feng Shao, Zongju Peng

Ningbo University, Faculty of Information Science and Engineering, Ningbo 315211, China

Mei Yu, Gangyi Jiang

Ningbo University, Faculty of Information Science and Engineering, Ningbo 315211, China

Nanjing University, National Key Lab of Software New Technology, Nanjing 210093, China

J. Electron. Imaging. 25(2), 023001 (Mar 07, 2016). doi:10.1117/1.JEI.25.2.023001
History: Received October 21, 2015; Accepted February 9, 2016
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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.

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Citation

Yang Song ; Mei Yu ; Gangyi Jiang ; Feng Shao and Zongju Peng
"Stereoscopic image quality assessment using disparity-compensated view filtering", J. Electron. Imaging. 25(2), 023001 (Mar 07, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.2.023001


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