A regularized optimization approach for AM-FM reconstructions

Paul Rodríguez, Victor Murray, Marios S. Pattichis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The AM-FM Dominant and Channelized Component Analysis (DCA and CCA respectively) [1], consist of applying a filter bank to the Hilbert-tranformed image, and then proceeding with the AM-FM demodulation of each band-pass filtered image. Whereas AM-FM reconstructions based on the CCA use a reasonably small number of locally coherent components, those based on the DCA only use one component: the estimates from the channel with the maximum amplitude estimate. Both types of reconstructions are known to produce noticeable visual artifacts. We propose a method, based on a regularized optimization of the estimates from the CCA, which attains a small number of locally coherent components and simultaneously enforces a piecewise smooth constrain for the amplitude functions. Moreover, this method offers high quality reconstructions when compared to standard CCA and DCA reconstructions and state of the art techniques [2].

Original languageEnglish
Title of host publicationConference Record of the 44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010
Pages219-221
Number of pages3
DOIs
StatePublished - 2010
Event44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010 - Pacific Grove, CA, United States
Duration: 7 Nov 201010 Nov 2010

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Conference

Conference44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010
Country/TerritoryUnited States
CityPacific Grove, CA
Period7/11/1010/11/10

Fingerprint

Dive into the research topics of 'A regularized optimization approach for AM-FM reconstructions'. Together they form a unique fingerprint.

Cite this