Iterative algorithms for lossy source coding
Name
79476754-MIT.pdf
Description
Full printable version
Size
2.76 MB
Format
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Checksum (MD5)
fd3ed4a8b1a159a04f48aa017107972a
Author(s)
Chandar, Venkat (Venkat Bala)
Advisor(s)
Gregory Wornell and Emin Martinian.
Date Issued
2006
Publisher
Massachusetts Institute of Technology
Abstract
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.
Description
Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references (p. 65-68).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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