Iterative algorithms for lossy source coding

This thesis explores the problems of lossy source coding and information embedding. For lossy source coding, we analyze low density parity check (LDPC) codes and low density generator matrix (LDGM) codes for quantization under a Hamming distortion. We prove that LDPC codes can achieve the rate-distortion function. We also show that the variable node degree of any LDGM code must become unbounded for these codes to come arbitrarily close to the rate-distortion bound. For information embedding, we introduce the double-erasure information embedding channel model. We develop capacity-achieving codes for the double-erasure channel model. Furthermore, we show that our codes can be efficiently encoded and decoded using belief propagation techniques. We also discuss a generalization of the double-erasure model which shows that the double-erasure model is closely related to other models considered in the literature.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Chandar, Venkat (Venkat Bala)

Advisor dc:contributor.advisor

• Gregory Wornell and Emin Martinian.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/36780

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/36780