Motion adaptive classified vector quantization for atm video coding

Jian Feng; Hassan Mehrpour; Kwok Tung Lo

doi:10.1109/30.391361

Motion adaptive classified vector quantization for atm video coding

Jian Feng, Hassan Mehrpour, Kwok Tung Lo

Research output: Journal article publication › Journal article › Academic research › peer-review

Abstract

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.

Original language	English
Pages (from-to)	322-326
Number of pages	5
Journal	IEEE Transactions on Consumer Electronics
Volume	41
Issue number	2
DOIs	https://doi.org/10.1109/30.391361
Publication status	Published - 1 Jan 1995

ASJC Scopus subject areas

Electrical and Electronic Engineering
Media Technology
Computer Networks and Communications

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10.1109/30.391361

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Motion adaptive classified vector quantization for atm video coding

Abstract

ASJC Scopus subject areas

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