Computational RAM implementation of an adaptive vector quantization algorithm for video compression

Research output: Contribution to journalArticle

Abstract

Vector Quantization (VQ) is a promising technique for low-bit rate image and video compression. Recently, adaptive VQ-based video compression algorithms have been reported in the literature. This paper proposes a new method which combines index-based motion estimation, and pattern-matching VQ for low-bit rate video compression. The proposed technique has been implemented on a ComputationalRAM (CRAM) SIMD structure.

Original languageEnglish (US)
Pages (from-to)294-295
Number of pages2
JournalUnknown Journal
StatePublished - 1995
Externally publishedYes

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Data Compression
Vector quantization
Random access storage
Image compression
Pattern matching
Motion estimation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

Cite this

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title = "Computational RAM implementation of an adaptive vector quantization algorithm for video compression",
abstract = "Vector Quantization (VQ) is a promising technique for low-bit rate image and video compression. Recently, adaptive VQ-based video compression algorithms have been reported in the literature. This paper proposes a new method which combines index-based motion estimation, and pattern-matching VQ for low-bit rate video compression. The proposed technique has been implemented on a ComputationalRAM (CRAM) SIMD structure.",
author = "Le, {T. M.} and Sethuraman Panchanathan",
year = "1995",
language = "English (US)",
pages = "294--295",
journal = "Scanning Electron Microscopy",
issn = "0586-5581",
publisher = "Scanning Microscopy International",

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