Astronomical image representation by the curvelet transform

2003/01/21 by J. L. Starck, Jean‐Luc Starck, D. L. Donoho +3 · 5 citations
Computer Science · #Image and Signal Denoising Methods #Medical Image Segmentation Techniques #Image Retrieval and Classification Techniques

paper · pdf · doi:10.1051/0004-6361:20021571

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.

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