Intra-Prediction Side-Information Reduction Based on Gradient Boundary

Abstract

Recent developments in intra-prediction show the advantage of increasing the number of prediction directions. This trend can be observed in most previous standards, and should remain in the future. However, increasing the number of intra-prediction directions incurs a non-negligible side-information bit-rate. To reduce this side-information bit-rate, we propose a method to adaptively decide whether to use a larger or smaller set of candidate intra-prediction directions by simply evaluating the maximum gradient magnitude, theoretically motivated by the prediction inaccuracy model. In this scenario, we can achieve most of the gain from using the larger intra-prediction direction set while only requiring a small amount of side-information. This method yields a significant BD-rate reduction on multiple resolutions of images using fixed block-size when implemented in a simplified HEVC-based encoder.