Complex Singular Value Decomposition based Stereoscopic Image Quality Assessment

被引：0
|
作者：
Wang, Xu [1 ]
Cao, Lei [1 ]
Ma, Lin [2 ]
Zhou, Yu [3 ]
Kwong, Sam [3 ]
机构：
[1] Shenzhen Univ, Coll Comp Sci & Software Engn, Shenzhen 518060, Peoples R China
[2] Hamel Noahs Ark Lab, Hong Kong, Hong Kong, Peoples R China
[3] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China
来源：
2016 30TH ANNIVERSARY OF VISUAL COMMUNICATION AND IMAGE PROCESSING (VCIP) | 2016年
基金：
中国国家自然科学基金;
关键词：
Complex Singular Value Decomposition; Stereoscopic Image Quality Assessment; VIDEO;
D O I：
暂无
中图分类号：
TB8 [摄影技术];
学科分类号：
0804 ;
摘要：
Designing a reliable and generic perceptual quality metric is a challenging issue in three-dimensional (3D) visual signal processing. Due to the limited knowledge on 3D perceptual, it is difficult to fuse the visual information of left and right views in an effective way. In this paper, we propose a complex singular value decomposition (CSVD) based stereoscopic image quality assessment (SIQA) metric. First, the corresponding blocks of the left/right view are grouped into complex representation (CR) block through the scale-invariant feature transform (SIFT) view matching process. Then we compute the CSVD coefficients of each CR block. Final, a CSVD based quality pooling stage is employed to predict the final visual quality of the distorted 3D image. Experimental results demonstrate that the proposed metric has good consistency with 3D perception of human.
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收藏
页数：4
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