Spatial and Temporal Adaptation of Interpolation Filter For Low Complexity Encoding/Decoding

Abstract

Compared to video coding with non-adaptive interpolation filtering, adaptive filters achieve higher compression ratios, with an increase in encoding and decoding complexity. In our earlier work, we significantly reduced the decoding complexities of adaptive filtering schemes with a minimal impact on the coding efficiency by making use of different filters and adapting them spatially and temporally. However, our previous scheme required high encoder complexity, as several encoding passes per frame were needed to analyze the input image and optimize the selection of interpolation filters. In this paper, a novel algorithm that does not require multiple encoding passes, but still give similar or better performance is proposed. This is achieved by using a modified decision making function that does not require full reconstruction of coded frame and use motion and prediction information more efficiently. In addition, we generalized our previous scheme by introducing additional filters, so that better Rate-Distortion-Complexity tradeoffs are possible. Experimental results show that up-to 50-70% reduction in interpolation complexity is achieved, with less than 0.13 dB penalty on coding efficiency.