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Proceedings Paper

Subband image coding using entropy-coded quantization
Author(s): Nariman Farvardin; Naoto Tanabe
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Paper Abstract

ABSTRACT In this paper we develop two entropy-coded subband image coding schemes. The difference between these schemes is the procedure used for encoding the lowest frequency subband: predictive coding is used in one system and transform coding in the other. Other subbands are encoded using zero-memory quantization. After a careful study of subband statistics, the quantization parameters, the corresponding Huffman codes and the bit allocation among subbands are all optimized. It is shown that both schemes perform considerably better than the scheme developed by Woods and O'Neil [2]. Roughly speaking, these new schemes perform the same as that in [2] at half the encoding rate. To make a complete comparison against the results in [2] , we have studied the performance of the two schemes developed here as well as that of [2] in the presence of channel noise. After developing a codeword packetization scheme, we demonstrate that the scheme in [2] exhibits significantly higher robustness against the transmission noise.

Paper Details

Date Published: 1 June 1990
PDF: 15 pages
Proc. SPIE 1244, Image Processing Algorithms and Techniques, (1 June 1990); doi: 10.1117/12.19508
Show Author Affiliations
Nariman Farvardin, Univ. of Maryland (United States)
Naoto Tanabe, Univ. of Maryland (Japan)

Published in SPIE Proceedings Vol. 1244:
Image Processing Algorithms and Techniques
Robert J. Moorhead; Keith S. Pennington, Editor(s)

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