Astronomical image and data analysis

By Jean-Luc Starck, Fionn Murtagh. 2002

487 citations recorded by the source corpus.

Subfields: Astronomy and Astrophysics, Computational Mechanics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/c645b829087d5282bf4d2c442f93fca8a516045e

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In Astronomy and Astrophysics

In Computational Mechanics

In Instrumentation

Citations in the corpus

Filament Identification through Mathematical Morphology (2015, methodology): “The decomposition is similar to the continuous form of the a trous wavelet algorithm (Starck & Murtagh 2006).”
Directly Observing the Galaxies Likely Responsible for Reionization (2016, background): “…used in astronomy for purposes such as de-noising images (Starck et al. 2002), analyzing the clustering of galaxies (Slezak et al. 1993; Escalera & MacGillivray 1995; Martínez et al. 2005), and detecting non-Gaussianity in the cosmic microwave background (Starck et al. 2004; Vielva et al. 2004).”
Deconvolution in Astronomy: A Review (2002, background): “The significant residual (Murtagh & Starck 1994; Starck & Murtagh 1994 ) is then”
Restoration of Poissonian Images Using Alternating Direction Optimization (2010, unknown): “Although the problem is convex, its very high dimensionality (when dealing with images) usually rules out the direct application of off-the-shelf optimization algorithms.”
Fast multiscale clustering and manifold identification (2006, unknown): “[29,30]), and detecting sparse background noise.”
The earliest phases of high-mass star formation: a 3 square degree millimeter continuum mapping of Cygnus X (2007, methodology): “For this purpose, we use a multiresolution program based on wavelet transforms (MRE, cf. Starck & Murtagh 2006).”
The Undecimated Wavelet Decomposition and its Reconstruction (2007, methodology): “This wavelet transformation is very well adapted to the analysis of images which contain isotropic objects such as in astronomy [11] or in biology [21].”