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Astronomical image representation by the curvelet transform

Starck, J. L. and Donoho, D. L. and Candès, E. J. (2003) Astronomical image representation by the curvelet transform. Astronomy & Astrophysics, 398 (2). pp. 785-800. ISSN 0004-6361. https://resolver.caltech.edu/CaltechAUTHORS:20180228-083442449

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Abstract

We outline digital implementations of two newly developed multiscale representation systems, namely, the ridgelet and curvelet transforms. We apply these digital transforms to the problem of restoring an image from noisy data and compare our results with those obtained via well established methods based on the thresholding of wavelet coefficients. We show that the curvelet transform allows us also to well enhance elongated features contained in the data. Finally, we describe the Morphological Component Analysis, which consists in separating features in an image which do not present the same morphological characteristics. A range of examples illustrates the results.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1051/0004-6361:20021571DOIArticle
https://www.aanda.org/articles/aa/abs/2003/05/aa2574/aa2574.htmlPublisherArticle
ORCID:
AuthorORCID
Donoho, D. L.0000-0003-1830-710X
Candès, E. J.0000-0001-9234-924X
Additional Information:© 2003 ESO. Received: 12 April 2002. Accepted: 29 October 2002. We are grateful to the referee for helpful comments on an earlier version.
Subject Keywords:methods: data analysis - techniques: image processing
Issue or Number:2
Record Number:CaltechAUTHORS:20180228-083442449
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20180228-083442449
Official Citation:Astronomical image representation by the curvelet transform J. L. Starck, D. L. Donoho and E. J. Candès A&A, 398 2 (2003) 785-800 DOI: https://doi.org/10.1051/0004-6361:20021571
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:84988
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:28 Feb 2018 17:43
Last Modified:03 Oct 2019 19:25

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