This website uses cookies to improve your experience. If you continue without changing your settings, you consent to our use of cookies in accordance with our cookie policy. You can disable cookies at any time.


Similarity index for seismic data sets using adaptive curvelets



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.