Macroblock Classification for Video Encoder Complexity Management

We describe a system for classifying macroblocks in order to reduce computational complexity in a block-based video encoder. Sequence statistics are used to predict macroblock type prior to coding, enabling selective computation of functions such as motion estimation, DCT and quantization. Results are presented for a “skip mode” prediction algorithm demonstrating that our approach can deliver substantial computational savings at the expense of a small reduction in rate-distortion performance.