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Title: Implementation of VQ algorithms on a reconfigurable array processor. Professional paper

Abstract

Vector quantization is being widely used in image data compression applications due to the facts that it is capable of achieving fractional bit rates with reasonable complexity and that the decoding is a very simple table look-up scheme. In image encoding, a vector quantizer accepts a block of pixels and outputs an address of the best matching tile stored in a codebook. The matching algorithm requires a large number of basic arithmetic operations in typical applications. Since real time coding is required in many video applications, the need for dedicated processing architectures arises naturally. This paper investigates the mapping of VQ algorithms onto an array processor to achieve near real-time compression of video images.

Authors:
;
Publication Date:
Research Org.:
Naval Ocean Systems Center, San Diego, CA (United States)
OSTI Identifier:
5217551
Report Number(s):
AD-A-236483/4/XAB
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; IMAGE PROCESSING; ALGORITHMS; ARRAY PROCESSORS; COMPRESSION; COMPUTER ARCHITECTURE; DATA PROCESSING; PARALLEL PROCESSING; PROGRAMMING; QUANTIZATION; REAL TIME SYSTEMS; MATHEMATICAL LOGIC; PROCESSING; 990200* - Mathematics & Computers

Citation Formats

Henderson, T B, and Thyagarajan, K S. Implementation of VQ algorithms on a reconfigurable array processor. Professional paper. United States: N. p., 1991. Web.
Henderson, T B, & Thyagarajan, K S. Implementation of VQ algorithms on a reconfigurable array processor. Professional paper. United States.
Henderson, T B, and Thyagarajan, K S. Wed . "Implementation of VQ algorithms on a reconfigurable array processor. Professional paper". United States.
@article{osti_5217551,
title = {Implementation of VQ algorithms on a reconfigurable array processor. Professional paper},
author = {Henderson, T B and Thyagarajan, K S},
abstractNote = {Vector quantization is being widely used in image data compression applications due to the facts that it is capable of achieving fractional bit rates with reasonable complexity and that the decoding is a very simple table look-up scheme. In image encoding, a vector quantizer accepts a block of pixels and outputs an address of the best matching tile stored in a codebook. The matching algorithm requires a large number of basic arithmetic operations in typical applications. Since real time coding is required in many video applications, the need for dedicated processing architectures arises naturally. This paper investigates the mapping of VQ algorithms onto an array processor to achieve near real-time compression of video images.},
doi = {},
url = {https://www.osti.gov/biblio/5217551}, journal = {},
number = ,
volume = ,
place = {United States},
year = {1991},
month = {5}
}

Technical Report:
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