Similarity index for seismic data sets using adaptive curvelets

نویسندگان

  • Hasan Al-Marzouqi
  • Ghassan AlRegib
چکیده

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.

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تاریخ انتشار 2014