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

T. M. Le; S. Panchanathan

doi:10.1109/30.468015

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

T. M. Le
, S. Panchanathan

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Vector Quantization (VQ) is a promising technique for lowbit rate image and video compression. Recently, adaptive VQ-based video compression algorithms have been reported in the literature. This paper proposes an adaptive codebook replenishment VQ algorithm using index-based motion estimation (AVQ+ME) for low-bit rate video compression. The proposed technique has been implemented on a Computational*RAM (C*RAM) SIMD structure.

Original language	English (US)
Pages (from-to)	738-747
Number of pages	10
Journal	IEEE Transactions on Consumer Electronics
Volume	41
Issue number	3
DOIs	https://doi.org/10.1109/30.468015
State	Published - Aug 1995
Externally published	Yes

ASJC Scopus subject areas

Media Technology
Electrical and Electronic Engineering

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10.1109/30.468015

Cite this

@article{6c803a2b855f4e65a92b73893ef5c5be,

title = "Computational RAM implementation of an adaptive vector quantization algorithm for video compression",

abstract = "Vector Quantization (VQ) is a promising technique for lowbit rate image and video compression. Recently, adaptive VQ-based video compression algorithms have been reported in the literature. This paper proposes an adaptive codebook replenishment VQ algorithm using index-based motion estimation (AVQ+ME) for low-bit rate video compression. The proposed technique has been implemented on a Computational*RAM (C*RAM) SIMD structure.",

author = "Le, \{T. M.\} and S. Panchanathan",

note = "Funding Information: This work was supported by the National Sciences and Engineering Research Council of Canada (NSERC) and Microelectronics Network (MICRONET) under the Network Centers of Excellence (NCE) program of the Government of Canada. The authors wish to thank E Idris for his valuable comments.",

year = "1995",

month = aug,

doi = "10.1109/30.468015",

language = "English (US)",

volume = "41",

pages = "738--747",

journal = "IEEE Transactions on Consumer Electronics",

issn = "0098-3063",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "3",

}

TY - JOUR

T1 - Computational RAM implementation of an adaptive vector quantization algorithm for video compression

AU - Le, T. M.

AU - Panchanathan, S.

N1 - Funding Information: This work was supported by the National Sciences and Engineering Research Council of Canada (NSERC) and Microelectronics Network (MICRONET) under the Network Centers of Excellence (NCE) program of the Government of Canada. The authors wish to thank E Idris for his valuable comments.

PY - 1995/8

Y1 - 1995/8

N2 - Vector Quantization (VQ) is a promising technique for lowbit rate image and video compression. Recently, adaptive VQ-based video compression algorithms have been reported in the literature. This paper proposes an adaptive codebook replenishment VQ algorithm using index-based motion estimation (AVQ+ME) for low-bit rate video compression. The proposed technique has been implemented on a Computational*RAM (C*RAM) SIMD structure.

AB - Vector Quantization (VQ) is a promising technique for lowbit rate image and video compression. Recently, adaptive VQ-based video compression algorithms have been reported in the literature. This paper proposes an adaptive codebook replenishment VQ algorithm using index-based motion estimation (AVQ+ME) for low-bit rate video compression. The proposed technique has been implemented on a Computational*RAM (C*RAM) SIMD structure.

UR - https://www.scopus.com/pages/publications/0029354830

UR - https://www.scopus.com/pages/publications/0029354830#tab=citedBy

U2 - 10.1109/30.468015

DO - 10.1109/30.468015

M3 - Article

SN - 0098-3063

VL - 41

SP - 738

EP - 747

JO - IEEE Transactions on Consumer Electronics

JF - IEEE Transactions on Consumer Electronics

IS - 3

ER -

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

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