A SPECTRAL APPROACH TO RECURSIVE END-TO-END DISTORTION ESTIMATION FOR SUB-PIXEL MOTION-COMPENSATED VIDEO CODING

Video Coding

Přednášející: Jingning Han, Autoři: Jingning Han, University of California Santa Barbara, United States; Vinay Melkote, Dolby Laboratories Inc., United States; Kenneth Rose, University of California Santa Barbara, United States

Error resilient video coding critically relies on the accuracy of end-to-end distortion estimation. An established solution, the recursive optimal per-pixel estimate (ROPE), is based on tracking the first and second moments of the decoder reconstructed pixels. This paper is focused on an alternative estimation approach, the spectral coefficient-wise optimal recursive estimate (SCORE), whose recursion is performed in the transform domain. The SCORE formulation is extended to derive a new technique for effective end-to-end distortion estimation, which accounts for sub-pixel motion compensation. Specifically, this technique exploits properties of the transform, such as coefficient de-correlation and energy compaction, to overcome ROPE's remaining shortcoming due to the proliferation of cross-correlation terms requiring excessive complexity or relatively crude approximations. Experiments show that the accuracy of SCORE matches ROPE in the full-pixel motion compensation setting, where ROPE is known to be optimal. More importantly, in the problematic setting of sub-pixel motion compensation, SCORE substantially outperforms ROPE and yields highly accurate distortion estimation.

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