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Proceedings Paper

Curvelet transform with adaptive tiling
Author(s): Hasan Al-Marzouqi; Ghassan AlRegib
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Paper Abstract

The curvelet transform is a recently introduced non-adaptive multi-scale transform that have gained popularity in the image processing field. In this paper, we study the effect of customized tiling of frequency content in the curvelet transform. Specifically, we investigate the effect of the size of the coarsest level and its relationship to denoising performance. Based on the observed behavior, we introduce an algorithm to automatically choose the optimal number of decompositions. Its performance shows a clear advantage, in denoising applications, when compared to default curvelet decomposition. We also examine how denoising is affected by varying the number of divisions per scale.

Paper Details

Date Published: 2 February 2012
PDF: 6 pages
Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 82950F (2 February 2012); doi: 10.1117/12.909111
Show Author Affiliations
Hasan Al-Marzouqi, Georgia Institute of Technology (United States)
Ghassan AlRegib, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 8295:
Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II
Karen O. Egiazarian; John Recker; Guijin Wang; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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