A Two-Level Classification-Based Approach to Inter Mode Decision in H.264/AVC

Abstract

The H.264/AVC standard achieves a high coding efficiency compared to previous standards. However, this gain is accomplished at great computational cost, with mode decision being one of the most demanding subsystems. In this paper, a two-level classification-based approach to the inter mode decision problem is proposed. A first classifier detects SKIP/Direct modes, while a second one is able to decide whether to use a large (16 × 16, 16 × 8, and 8 × 16) or a small mode (8 × 8, 8 × 4, 4 × 8, and 4 × 4). The suggested classifiers are binary and linear, and the input features in the classifiers have been carefully selected. A novel cost function that pays more attention to the most critical samples during the classifier training process has been designed. The experimental results show an average computational savings of 60% of the total encoding time with respect to JM10.2 over a comprehensive variety of sequences and formats. This is achieved with negligible degradation in rate-distortion performance and compares favorably with state-of-the-art fast mode decision methods. Furthermore, the proposed method has been successfully assessed at different levels of complexity reduction.