A Hierarchical Framework for Fast Macroblock Prediction Mode Decision in H.264

Many intra and inter prediction modes for macroblock are supported in the latest video compression standard H.264. Using the powerful Lagrangian minimization tool such as rate-distortion optimization, the mode with the optimal rate-distortion performance is determined. This achieves highest possible coding efficiency, but total calculation of cost for all candidate modes results in much higher computational complexity. In this paper, we propose a hierarchical framework for fast macroblock prediction mode decision in H.264 encoders. It is based on hierarchical mode classification method which assists fast mode decision by pre-selecting the class for macroblock using the extracted spatial and temporal features of macroblock. Since tests for many modes of non-selected classes will be skipped, much computation of rate-distortion optimization can be saved. Experimental results show that the proposed method can reduce the execution time of mode decision by 85% on the average without perceivable loss in coding rate and quality.