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Perception-based adaptive quantization for transform-domain Wyner-Ziv video coding

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Abstract

Distributed video coding (DVC) is desirable for encoding systems with tight power or computational constraints, for which the popular practical solution is transform-domain Wyner-Ziv video coding (TD-WZVC). To achieve the similar coding performance with H.264/AVC, quantization is a key factor in TD-WZVC. Practically, the quantization matrix is trained offline and remains fixed value during coding. Optimal rate-distortion (RD) performance cannot be achieved due to the varying quality of side information (SI) frame. In this paper, a novel model of perceptual distortion probability is developed to estimate the perceptual distortion of SI frame and to derive the target perceptual distortion. With the two perceptual distortion probabilities, three components (i.e. quality of SI frame, perceptual features and RD optimization) are integrated to determine the optimal quantization matrix adaptively, which improves the coding performance. Extensive experiments demonstrate that the proposed scheme can adaptively determine proper quantization matrix online and achieve similar visual quality with less bit-rate, as compared to other adaptive quantization schemes in TD-WZVC.

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Acknowledgments

This work described in this paper was supported by the NSFC (Grant No. 60972111, 61036008, 61071184, 61373121), Research Funds for the Doctoral Program of Higher Education of China (No. 20100184120009, 20120184110001), Program for Sichuan Provincial Science Fund for Distinguished Young Scholars (No. 2012JQ0029, 13QNJJ0149), and the Fundamental Research Funds for the Central Universities (Project no. SWJTU09CX032, SWJTU10CX08, SWJTU11ZT08).

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  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China

    Lei Zhang, Qiang Peng & Xiao Wu

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  1. Lei Zhang
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  2. Qiang Peng
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  3. Xiao Wu
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Correspondence to Lei Zhang.

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Zhang, L., Peng, Q. & Wu, X. Perception-based adaptive quantization for transform-domain Wyner-Ziv video coding. Multimed Tools Appl 76, 16699–16725 (2017). https://doi.org/10.1007/s11042-016-3947-4

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  • DOI: https://doi.org/10.1007/s11042-016-3947-4

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