Title :
Data augmentation for galaxy density map reconstruction
Author :
Dupe, Francois-Xavier ; Fadili, M.J. ; Starck, Jean-Luc
Author_Institution :
CEA, Gif-sur-Yvette, France
Abstract :
The matter density is an important knowledge for today cosmology as many phenomena are linked to matter fluctuations. However, this density is not directly available, but estimated through lensing maps or galaxy surveys. In this article, we focus on galaxy surveys which are incomplete and noisy observations of the galaxy density. Incomplete, as part of the sky is unobserved or unreliable. Noisy as they are count maps degraded by Poisson noise. Using a data augmentation method, we propose a two-step method for recovering the density map, one step for inferring missing data and one for estimating the density. The results show that the missing areas are efficiently inferred and the statistical properties of the maps are preserved.
Keywords :
astronomy computing; cosmology; data handling; galaxies; statistical analysis; Poisson noise; cosmology; data augmentation method; density estimation; galaxy density map reconstruction; galaxy surveys; map statistical properties; matter density; missing data inferring; two-step method; Conferences; Estimation; Harmonic analysis; Image processing; Log-normal distribution; Noise; Optimization; Bayesian framework; Data augmentation; Inpainting; Poisson noise; Sparse representation;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6115674