On rate distortion optimization using SSIM

  • Yeo C
  • Tan H
  • Tan Y
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Abstract

In this paper, we present a method for performing rate-distortion optimization (RDO) using a perceptual visual quality metric, the structural similarity index (SSIM), as the target of optimization. Rate-distortion optimization is widely used in modern video codecs to make various encoder decisions to optimize the rate-distortion tradeoff. Typically, the distortion measure used is either sum-of-square error or sum-of-absolute distance, both of which are convenient when used in the RDO framework but not always reflective of a perceptual visual quality. We show that SSIM can be used as the distortion metric in the RDO framework in a simple, yet effective, manner by scaling the Lagrange multiplier used in RDO based on the local variance in that region. The experimental results on the H.264/AVC reference software show that compared to traditional RDO approaches, for the same SSIM score, the proposed approach can achieve an average rate reduction of about 9% and 14% for random access and low-delay encoding configurations. At the same time, there is no significant change in the encoding runtime.

Author-supplied keywords

  • Rate-distortion optimization (RDO)
  • Structural similarity index (SSIM)
  • Terms-Perceptual-based coding
  • Video coding

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Authors

  • Chuohao Yeo

  • Hui Li Tan

  • Yih Han Tan

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