DocumentCode :
1476995
Title :
An efficient VLSI architecture for 2-D wavelet image coding with novel image scan
Author :
Lafruit, Gauthier ; Catthoor, Francky ; Cornelis, Jan P H ; De Man, Hugo J.
Author_Institution :
IMEC, Heverlee, Belgium
Volume :
7
Issue :
1
fYear :
1999
fDate :
3/1/1999 12:00:00 AM
Firstpage :
56
Lastpage :
68
Abstract :
A folded very large scale integration (VLSI) architecture is presented for the implementation of the two-dimensional discrete wavelet transform, without constraints on the choice of the wavelet-filter bank. The proposed architecture is dedicated to flexible block-oriented image processing, such as adaptive vector quantization used in wavelet image coding. We show that reading the image along a two-dimensional (2-D) pseudo-fractal scan creates a very modular and regular data flow and, therefore, considerably reduces the folding complexity and memory requirements for VLSI implementation. This leads to significant area savings for on-chip storage (up to a factor of two) and reduces the power consumption. Furthermore, data scheduling and memory management remain very simple. The end result is an efficient VLSI implementation with a reduced area cost compared to the conventional approaches, reading the input data line by line.
Keywords :
VLSI; digital signal processing chips; discrete wavelet transforms; fractals; image coding; vector quantisation; 2D wavelet image coding; adaptive vector quantization; data scheduling; folded VLSI architecture; image processing; memory management; pseudo-fractal image scan; two-dimensional discrete wavelet transform; wavelet filter bank; Application specific integrated circuits; Bandwidth; Costs; Discrete wavelet transforms; Energy consumption; Image coding; Image processing; Signal processing algorithms; Vector quantization; Very large scale integration;
fLanguage :
English
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-8210
Type :
jour
DOI :
10.1109/92.748201
Filename :
748201
Link To Document :
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