Similarity index for seismic data sets using adaptive curvelets

Hasan Al-Marzouqi, Ghassan AlRegib

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

1 Scopus citations

Abstract

In this paper, we propose a distance measure to evaluate visual similarity between two images. The algorithm searches for adaptive curvelet parameters that better represent a reference image. Next, the distance between the reference image and other images is computed as a weighted sum of distances between histograms of adaptive curvelet coefficients. The algorithm is tested on a data set of exemplary seismic activities. The developed measure is shown to be effective in extracting correct matches from the data set.

Original languageBritish English
Title of host publicationSociety of Exploration Geophysicists International Exposition and 84th Annual Meeting SEG 2014
PublisherSociety of Exploration Geophysicists
Pages1709-1713
Number of pages5
ISBN (Print)9781634394857
DOIs
StatePublished - 2014
EventSociety of Exploration Geophysicists International Exposition and 84th Annual Meeting SEG 2014 - Denver, United States
Duration: 26 Oct 201431 Oct 2014

Publication series

NameSociety of Exploration Geophysicists International Exposition and 84th Annual Meeting SEG 2014

Conference

ConferenceSociety of Exploration Geophysicists International Exposition and 84th Annual Meeting SEG 2014
Country/TerritoryUnited States
CityDenver
Period26/10/1431/10/14

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