Spatio-temporal prediction in video coding by best approximation

TL;DR

This paper introduces a fast, two-stage spatio-temporal prediction algorithm for video coding that significantly reduces data rates by combining motion compensation with a novel spatial refinement method.

Contribution

The paper presents a new efficient spatio-temporal prediction method with minimal iteration, improving speed and reducing data rates in H.264/AVC video coding.

Findings

Achieves up to 13% data rate reduction in tested sequences.

Speedup factor of 17 over previous refinement algorithms.

Effective exploitation of spatial and temporal correlations.

Abstract

Within the scope of this contribution we propose a novel efficient spatio-temporal prediction algorithm for video coding. The algorithm operates in two stages. First, motion compensation is performed on the block to be predicted in order to exploit temporal correlations. Afterwards, in order to exploit spatial correlations, this preliminary estimate is spatially refined by forming a joint model of the motion compensated block and spatially adjacent already decoded blocks. Compared to an earlier refinement algorithm, the novel one only needs very little iteration, leading to a speedup of factor 17. The implementation of this new algorithm into the H.264/AVC leads to a maximum reduction in data rate of up to nearly 13% for the considered sequences.