2008/09/15 by R. B. Barreiro, P. Vielva, C. Hernández-Monteagudo +3
Mathematics · Physics and Astronomy · #Algorithm #Computer science #Computer vision #Cosmic microwave background #Cosmology and Gravitation Theories #Covariance #Filter (signal processing) #Galaxies: Formation, Evolution, Phenomena #Matched filter #Mathematics #Optics #Physics #Radio Astronomy Observations and Technology #SIGNAL (programming language) #Statistics #Wiener filter #astro-ph
paper · pdf · doi:10.1109/jstsp.2008.2005350
8 pages, 6 figures, accepted for publication in the IEEE Journal of Selected Topics in Signal Processing
arxiv created 2008/09/15 · openalex publication_date 2008/10/01 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The extraction of a signal from some observational data sets that contain different contaminant emissions, often at a greater level than the signal itself, is a common problem in astrophysics and cosmology. The signal can be recovered, for instance, using a simple Wiener filter. However, in certain cases, additional information may also be available, such as a second observation which correlates to a certain level with the sought signal. In order to improve the quality of the reconstruction, it would be useful to include as well this additional information. Under these circumstances, we have constructed a linear filter, the linear covariance-based filter, that extracts the signal from the data but takes also into account the correlation with the second observation. To illustrate the performance of the method, we present a simple application to reconstruct the so-called Integrated Sachs-Wolfe effect from simulated observations of the cosmic microwave background and of catalogues of galaxies.