AI

An optimized template matching approach to intra coding in video/image compression

Abstract

The template matching prediction is an established approach to intra-frame coding that makes use of previously coded pixels in the same frame for reference. It compares the previously reconstructed upper and left boundaries in searching from the reference area the best matched block for prediction, and hence eliminates the need of sending additional information to reproduce the same prediction at decoder. In viewing the image signal as an auto-regressive model, this work is premised on the fact that pixels closer to the known block boundary are better predicted than those far apart. It significantly extends the scope of the template matching approach, which is typically followed by a conventional discrete cosine transform (DCT) for the prediction residuals, by employing an asymmetric discrete sine transform (ADST), whose basis functions vanish at the prediction boundary and reach maximum magnitude at far end, to fully exploit statistics of the residual signals. It was experimentally shown that the proposed scheme provides substantial coding performance gains on top of the conventional template matching method over the baseline.