Perfect Reconstructing Nonlinear Filter Banks

Dinei A. Florencio and Ronald Schafer

Abstract

Perfect reconstruction (PR) filter banks have found numerous

applications, and have received much attention in

the literature. For linear filter banks, necessary and sufficient

conditions for PR have been established for most

practical situations. Recently, nonlinear filter banks have

been proposed for image coding applications. These filters

are generally simple, and produce better results than linear

filters of same complexity. Nevertheless, the lack of general

PR conditions limits these filters to cases where one of the

filters is the identity. In this paper, we present a framework

that allows, for the first time, the design of PR nonlinear

filter banks including (non-trivial) filters on all channels.

Although the framework does not include all nonlinear PR

filter banks, it does include all previously published nonlinear

filter banks, as well as all linear ones. This framework

suggest new possibilities for the design of nonlinear PR filter

banks.

Details

Publication typeInproceedings
Published inICASSP
PublisherIEEE SPS
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