Determining optimum subband edges for signal compression

Jana, Soumya and Makur, Anamitra (2002) Determining optimum subband edges for signal compression. In: 1997 International Conference on Information, Communications and Signal Processing - Trends in Information Systems Engineering and Wireless Multimedia Communications, 9-12 Sep 1997 , Singapore, Singapore.

PDF Determining_Optimum.pdf - Published Version Restricted to Registered users only Download (412kB) | Request a copy

Abstract

The coding gain in subband coding, a popular technique for achieving signal compression, depends on how the input signal spectrum is decomposed into subbands. The optimality of such decomposition is conventionally addressed by designing appropriate filter banks. The issue of optimal decomposition of the input spectrum is addressed by choosing the set of band that, for a given number of bands, will achieve maximum coding gain. A set of necessary conditions for such optimality is derived, and an algorithm to determine the optimal band edges is then proposed. These band edges along with ideal filters, achieve the upper bound of coding gain for a given number of bands. It is shown that with ideal filters, as well as with realizable filters for some given effective length, such a decomposition system performs better than the conventional nonuniform binary tree-structured decomposition in some cases for AR sources as well as images

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	Copyright 1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	16 Mar 2012 07:23
Last Modified:	16 Mar 2012 07:23
URI:	http://eprints.iisc.ac.in/id/eprint/43930

Actions (login required)

View Item