Video Coding Using Spatially Varying Transform

In this paper, a novel algorithm called spatially varying transform (SVT) is proposed to improve the coding efficiency of video coders. SVT enables video coders to vary the position of the transform block, unlike state-of-art video codecs where the position of the transform block is fixed. In addition to changing the position of the transform block, the size of the transform can also be varied within the SVT framework, to better localize the prediction error so that the underlying correlations are better exploited. It is shown in this paper that by varying the position of the transform block and its size, characteristics of prediction error are better localized, and the coding efficiency is thus improved. The proposed algorithm is implemented and studied in the H.264/AVC framework. We show that the proposed algorithm achieves 5.85% bitrate reduction compared to H.264/AVC on average over a wide range of test set. Gains become more significant at medium to high bitrates for most tested sequences and the bitrate reduction may reach 13.50%, which makes the proposed algorithm very suitable for future video coding solutions focusing on high fidelity video applications. The gain in coding efficiency is achieved with a similar decoding complexity which makes the proposed algorithm easy to be incorporated in video codecs. However, the encoding complexity of SVT can be relatively high because of the need to perform a number of rate distortion optimization (RDO) steps to select the best location parameter (LP), which indicates the position of the transform. In this paper, a novel low complexity algorithm is also proposed, operating on a macroblock and a block level, to reduce the encoding complexity of SVT. Experimental results show that the proposed low complexity algorithm can reduce the number of LPs to be tested in RDO by about 80% with only a marginal penalty in the coding efficiency.