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Data Compression Conference (DCC'06)
Trellis Based Variable Rate Residual Image Coding over Noisy Channels
Snowbird, Utah
March 28-March 30
ISBN: 0-7695-2545-8
ASCII Text
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Tomas Eriksson, Norbert Goertz, Mirek Novak, John B. Anderson, "Trellis Based Variable Rate Residual Image Coding over Noisy Channels," Data Compression Conference, pp. 252-261, Data Compression Conference (DCC'06), 2006.
 
 
BibTex
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@article{ 10.1109/DCC.2006.80,
author = {Tomas Eriksson and Norbert Goertz and Mirek Novak and John B. Anderson},
title = {Trellis Based Variable Rate Residual Image Coding over Noisy Channels},
journal ={Data Compression Conference},
volume = {0},
year = {2006},
issn = {1068-0314},
pages = {252-261},
doi = {http://doi.ieeecomputersociety.org/10.1109/DCC.2006.80},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Data Compression Conference
TI - Trellis Based Variable Rate Residual Image Coding over Noisy Channels
SN - 1068-0314
SP252
EP261
A1 - Tomas Eriksson,
A1 - Norbert Goertz,
A1 - Mirek Novak,
A1 - John B. Anderson,
PY - 2006
KW - Image coding
KW - Trellis quantization
KW - Model-residual approach
KW - Joint source and channel coding.
VL - 0
JA - Data Compression Conference
ER -
 
Tomas Eriksson, The University of Edinburgh, UK
Norbert Goertz, The University of Edinburgh, UK
Mirek Novak, Lund University, Sweden
John B. Anderson, Lund University, Sweden
We consider the lossy image compression problem and propose a model-residual approach. Polynomial basis images encode the model image and powerful new trellis codes quantize the residual part. A simple bit allocation scheme determines the residual bit rates and a variety of rates are attainable without entropy coding. The trellis structure is also used to form a joint source and channel coding scheme for the residual components. Results are shown for the 0.4-1.6 bits per pixel region. Comparisons are made to several state-of-theart techniques and show that the proposed scheme is very competitive.
Index Terms:
Image coding, Trellis quantization, Model-residual approach, Joint source and channel coding.
Citation:
Tomas Eriksson, Norbert Goertz, Mirek Novak, John B. Anderson, "Trellis Based Variable Rate Residual Image Coding over Noisy Channels," dcc, pp.252-261, Data Compression Conference (DCC'06), 2006
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