Efficient Predictive Coding of Intra Prediction Modes

TL;DR

This paper introduces a novel, context-based coding scheme for intra prediction modes in video codecs, utilizing a genetic algorithm to optimize bitrate reduction while maintaining efficiency.

Contribution

It presents a new coding scheme for intra prediction modes that combines prediction, clustering, and coding steps optimized by a genetic algorithm, improving compression efficiency.

Findings

Significant bitrate reductions achieved in HEVC standard.

Maintains coding efficiency under the JEM codec.

Binary tree-based coding scheme outperforms previous methods.

Abstract

The high efficiency video coding (HEVC) standard and the joint exploration model (JEM) codec incorporate 35 and 67 intra prediction modes (IPMs) respectively, which are essential for efficient compression of Intra coded blocks. These IPMs are transmitted to the decoder through a coding scheme. In our paper, we present an innovative approach to construct a dedicated coding scheme for IPM based on contextual information. This approach comprises three key steps: prediction, clustering, and coding, each of which has been enhanced by introducing new elements, namely, labels for prediction, tests for clustering, and codes for coding. In this context, we have proposed a method that utilizes a genetic algorithm to minimize the rate cost, aiming to derive the most efficient coding scheme while leveraging the available labels, tests, and codes. The resulting coding scheme, expressed as a binary tree, achieves the highest coding efficiency for a given level of complexity. In our experimental evaluation under the HEVC standard, we observed significant bitrate gains while maintaining coding efficiency under the JEM codec. These results demonstrate the potential of our approach to improve compression efficiency, particularly under the HEVC standard, while preserving the coding efficiency of the JEM codec.