Lossy compression of exponential and laplacian sources using expansion coding

Hongbo Si, Onur Ozan Koyluoglu, Sriram Vishwanath

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A general method of source coding is proposed in this paper, which enables one to reduce the problem of compressing an analog (continuous-valued) source to a set of much simpler problems, compressing discrete sources. Specifically, the focus is on lossy compression of exponential and Laplace sources, which are represented as set of discrete variables through a finite alphabet expansion. Due to the decomposability property of such sources, the resulting random variables post expansion are independent and discrete. Thus, these variables can be considered as independent discrete source coding problems, and the original problem is reduced to coding over these sources with a total distortion constraint. Any feasible solution to this resulting optimization problem corresponds to an achievable rate distortion pair of the original continuous-valued source compression problem. Although finding the optimal solution for a given distortion is not a tractable task, we show that, via a heuristic choice, our expansion coding scheme still presents a good performance in the low distortion regime. Further, by adopting low-complexity codes designed for discrete source coding, the total coding complexity can be reduced for practical implementations.

Original languageEnglish (US)
Title of host publicationIEEE International Symposium on Information Theory - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3052-3056
Number of pages5
ISBN (Print)9781479951864
DOIs
StatePublished - 2014
Event2014 IEEE International Symposium on Information Theory, ISIT 2014 - Honolulu, HI, United States
Duration: Jun 29 2014Jul 4 2014

Other

Other2014 IEEE International Symposium on Information Theory, ISIT 2014
CountryUnited States
CityHonolulu, HI
Period6/29/147/4/14

Fingerprint

Lossy Compression
Coding
Source Coding
Random variables
Decomposability
Discrete Variables
Rate-distortion
Laplace
Low Complexity
Compression
Optimal Solution
Random variable
Heuristics
Optimization Problem
Analogue

ASJC Scopus subject areas

  • Applied Mathematics
  • Modeling and Simulation
  • Theoretical Computer Science
  • Information Systems

Cite this

Si, H., Koyluoglu, O. O., & Vishwanath, S. (2014). Lossy compression of exponential and laplacian sources using expansion coding. In IEEE International Symposium on Information Theory - Proceedings (pp. 3052-3056). [6875395] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2014.6875395

Lossy compression of exponential and laplacian sources using expansion coding. / Si, Hongbo; Koyluoglu, Onur Ozan; Vishwanath, Sriram.

IEEE International Symposium on Information Theory - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 3052-3056 6875395.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Si, H, Koyluoglu, OO & Vishwanath, S 2014, Lossy compression of exponential and laplacian sources using expansion coding. in IEEE International Symposium on Information Theory - Proceedings., 6875395, Institute of Electrical and Electronics Engineers Inc., pp. 3052-3056, 2014 IEEE International Symposium on Information Theory, ISIT 2014, Honolulu, HI, United States, 6/29/14. https://doi.org/10.1109/ISIT.2014.6875395
Si H, Koyluoglu OO, Vishwanath S. Lossy compression of exponential and laplacian sources using expansion coding. In IEEE International Symposium on Information Theory - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. p. 3052-3056. 6875395 https://doi.org/10.1109/ISIT.2014.6875395
Si, Hongbo ; Koyluoglu, Onur Ozan ; Vishwanath, Sriram. / Lossy compression of exponential and laplacian sources using expansion coding. IEEE International Symposium on Information Theory - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 3052-3056
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