Motion adaptive classified vector quantization for ATM video coding

In this paper, a two-layer motion adaptive classified vector quantizer (MACVQ) is proposed for ATM video coding. The proposed method classifies image blocks into three different motion classes: slow-motion, medium-motion and fast-motion. Specified vector quantizers are then designed to encode different motion blocks. A simple edge-based classified vector quantizer is developed to encode the motion-compensated prediction (MCP) error. Compared with the MPEG-type DCT interframe coder, the proposed MACVQ coder has better MSE performance and less accumulation error between consecutive frames.<
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