2005/08/15 by V. J. Martinez, Vicent J. Martı́nez, Jean‐Luc Starck +10 · 2 citations
Computer Science · Mathematics · Physics and Astronomy · #Artificial intelligence #Astrophysics #Computer science #Distribution (mathematics) #Field (mathematics) #Galaxies: Formation, Evolution, Phenomena #Galaxy #Gaussian #Geology #Geometry #Image and Signal Denoising Methods #Mathematical analysis #Mathematics #Morphology (biology) #Noise reduction #Pattern recognition (psychology) #Physics #Point (geometry) #Pure mathematics #Scientific Research and Discoveries #Statistical physics #Wavelet #astro-ph
paper · pdf · doi:10.1086/497125
published as Astrophys.J.634:744-755,2005 · Accepted for publication in ApJ
arxiv created 2005/08/15 · openalex publication_date 2005/11/22 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We have developed a method based on wavelets to obtain the true underlying smooth density from a point distribution. The goal has been to reconstruct the density field in an optimal way, ensuring that the morphology of the reconstructed field reflects the true underlying morphology of the point field, which, as the galaxy distribution, has a genuinely multiscale structure, with near-singular behavior on sheets, filaments, and hot spots. If the discrete distributions are smoothed using Gaussian filters, the morphological properties tend to be closer to those expected for a Gaussian field. The use of wavelet denoising provides us with a unique and more accurate morphological description.