Binocular vision based objective quality assessment method for stereoscopic images

被引:0
|
作者
Gangyi Jiang
Junming Zhou
Mei Yu
Yun Zhang
Feng Shao
Zongju Peng
机构
[1] Ningbo University,Faculty of Information Science and Engineering
[2] Institute of Computing Technology,undefined
[3] Chinese Academic of Sciences,undefined
[4] Shenzhen Institutes of Advanced Technology,undefined
[5] Chinese Academy of Sciences,undefined
来源
关键词
Stereoscopic image; Objective quality assessment; Human visual system; Binocular fusion; Binocular suppression;
D O I
暂无
中图分类号
学科分类号
摘要
Human visual system (HVS) can perceive the difference between two retinal images to create a mental image with depth perception, which is the result of two binocular interactions, i.e., binocular fusion and suppression. According to perceptual attributes of binocular interactions, in this paper, a full-reference stereoscopic image quality assessment (SIQA) method is proposed based on the mechanisms of binocular fusion and suppression. There are two kinds of information in stereoscopic images: monocular information which is visible in only one view, and binocular information which is visible in two views. HVS adopts two ways to deal with the binocular information, one is binocular fusion which deals with the information with similar content and small disparity, the other is binocular suppression which deals with the information with dissimilar content or large disparity. Therefore, the proposed method firstly divides a distorted stereoscopic image into occluded, pseudo-binocular fusion and pseudo-binocular suppression regions. Then three methods are respectively adopted to assess the quality of the three regions and the three quality indices combine into one to represent the overall quality of the distorted stereoscopic image. Finally, the predictive performance of the proposed method is evaluated and compared with existing methods in terms of consistency, cross-image and cross-distortion, and robustness. Experimental results show that the proposed SIQA method outperforms other methods and can predict human visual perception of stereoscopic image more accurately.
引用
收藏
页码:8197 / 8218
页数:21
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