Motion adaptive classified vector quantization for atm video coding

Jian Feng, Hassan Mehrpour, Kwok Tung Lo

Research output: Journal article publicationJournal articleAcademic researchpeer-review


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 languageEnglish
Pages (from-to)322-326
Number of pages5
JournalIEEE Transactions on Consumer Electronics
Issue number2
Publication statusPublished - 1 Jan 1995

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Media Technology
  • Computer Networks and Communications


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