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Title: Implementation of VG algorithms on a reconfigurable array processor

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 realtime coding is required in many video applications, the need for dedicated processing architectures arises naturally. This reprint investigates the mapping of VQ algorithms onto an array processor to achieve near realtime compression of video images.

Authors:
;
Publication Date:
Research Org.:
Naval Ocean Systems Center, San Diego, CA (USA)
OSTI Identifier:
5673441
Report Number(s):
AD-A-230407/9/XAB
Resource Type:
Technical Report
Resource Relation:
Other Information: Pub. in Proceedings of the Annual Conference on Signals, Systems and Computers (24th) Nov 90
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ARRAY PROCESSORS; ALGORITHMS; COMPUTER ARCHITECTURE; DATA ACQUISITION; IMAGE PROCESSING; IMAGES; PARALLEL PROCESSING; QUANTIZATION; REAL TIME SYSTEMS; VECTOR PROCESSING; MATHEMATICAL LOGIC; PROCESSING; PROGRAMMING; 990200* - Mathematics & Computers

Citation Formats

Henderson, T B, and Thyagarajan, K S. Implementation of VG algorithms on a reconfigurable array processor. United States: N. p., 1990. Web.
Henderson, T B, & Thyagarajan, K S. Implementation of VG algorithms on a reconfigurable array processor. United States.
Henderson, T B, and Thyagarajan, K S. Sat . "Implementation of VG algorithms on a reconfigurable array processor". United States.
@article{osti_5673441,
title = {Implementation of VG algorithms on a reconfigurable array processor},
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 realtime coding is required in many video applications, the need for dedicated processing architectures arises naturally. This reprint investigates the mapping of VQ algorithms onto an array processor to achieve near realtime compression of video images.},
doi = {},
url = {https://www.osti.gov/biblio/5673441}, journal = {},
number = ,
volume = ,
place = {United States},
year = {1990},
month = {12}
}

Technical Report:
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