Stereoscopic Image Quality Assessment by Learning Non-negative Matrix Factorization-based Color Visual Characteristics and Considering Binocular Interactions

	Stereoscopic Image Quality Assessment by Learning Non-negative Matrix Factorization-based Color Visual Characteristics and Considering Binocular Interactions
	Jiang, Gangyi; Xu, Haiyong; Yu, Mei; Luo, Ting; Zhang, Yun
刊名	Journal of Visual Communication and Image Representation
	2017
文献子类	期刊论文
英文摘要	In this paper, we propose a novel stereoscopic image quality assessment (SIQA) method by learning non-negative matrix factorization (NMF)-based color visual characteristics for monocular perception and considering binocular interactions. In training phase, a feature basis matrix is learned based on NMF by considering color information and a feature detector is designed by performing Schmidt orthogonalization on the feature basis matrix. In construction of SIQA phase, for monocular perception, visual saliency regions are selected and parts-based feature similarity indexes of left and right views based on the feature vectors extracted by the feature detector are calculated. For binocular interactions, we calculate cyclopean feature similarity index by considering binocular fusion and rivalry. Finally, support vector regression is used to simulate nonlinear relationship between monocular perception and binocular interactions. Experimental results on LIVE 3D image databases and NBU 3D IQA database demonstrate that the proposed SIQA method is more consistent with human perception
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12462]
专题	深圳先进技术研究院_数字所
作者单位	Journal of Visual Communication and Image Representation
推荐引用方式 GB/T 7714	Jiang, Gangyi,Xu, Haiyong,Yu, Mei,et al. Stereoscopic Image Quality Assessment by Learning Non-negative Matrix Factorization-based Color Visual Characteristics and Considering Binocular Interactions[J]. Journal of Visual Communication and Image Representation,2017.
APA	Jiang, Gangyi,Xu, Haiyong,Yu, Mei,Luo, Ting,&Zhang, Yun.(2017).Stereoscopic Image Quality Assessment by Learning Non-negative Matrix Factorization-based Color Visual Characteristics and Considering Binocular Interactions.Journal of Visual Communication and Image Representation.
MLA	Jiang, Gangyi,et al."Stereoscopic Image Quality Assessment by Learning Non-negative Matrix Factorization-based Color Visual Characteristics and Considering Binocular Interactions".Journal of Visual Communication and Image Representation (2017).