Rate distortion optimization for stereoscopic video coding based on joint of binocular just-noticeable distortion and structural similarity index metric

Ning Xu; Xiangzhong Fang; Ci Wang; Haibing Yin

doi:10.1117/1.JEI.27.4.043039

7 August 2018 Rate distortion optimization for stereoscopic video coding based on joint of binocular just-noticeable distortion and structural similarity index metric

Ning Xu, Xiangzhong Fang, Ci Wang, Haibing Yin

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 4, 043039 (August 2018). https://doi.org/10.1117/1.JEI.27.4.043039

Abstract

In video coding, the Lagrange-based rate distortion optimization (RDO) plays important roles in improving coding efficiency. We proposed a method to improve the RDO of stereoscopic video coding. It uses two independent perception-based distortion metrics for the left and right views, as the distortion in the RDO. The distortion metric of the right view is to measure binocular perceptual distortion of the two views. The distortion metric of the left view is to measure two-dimensional (2-D) perceptual distortion of the left view. Both distortion metrics are developed based on the structural similarity index metric (SSIM) that is weighted by visual sensitivity. A binocular just-noticeable distortion (JND) model is proposed to measure binocular visual sensitivity for the right view. The commonly used 2-D JND models are adopted for the left view. In addition, a 1/SSIM-based rate-distortion (R-D) model is improved based the proposed distortion metrics. Based on it, the Lagrange multiplier is then derived according to the R-D theory. The experiments demonstrate that the proposed method has better performance than other perceptual RDO methods. Subjective evaluations also show that it can achieve better perceptual quality with less bit rate.

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Ning Xu, Xiangzhong Fang, Ci Wang, and Haibing Yin "Rate distortion optimization for stereoscopic video coding based on joint of binocular just-noticeable distortion and structural similarity index metric," Journal of Electronic Imaging 27(4), 043039 (7 August 2018). https://doi.org/10.1117/1.JEI.27.4.043039

Received: 7 April 2018; Accepted: 13 July 2018; Published: 7 August 2018

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KEYWORDS

Distortion

Video coding

Video

Visualization

Visual process modeling

Image quality

Computer programming

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