Multichannel Poisson denoising and deconvolution on the sphere : Application to the Fermi Gamma Ray Space Telescope
arXiv:1206.2787 · doi:10.1051/0004-6361/201118234
Abstract
A multiscale representation-based denoising method for spherical data contaminated with Poisson noise, the multiscale variance stabilizing transform on the sphere (MS-VSTS), has been previously proposed. This paper first extends this MS-VSTS to spherical two and one dimensions data (2D-1D), where the two first dimensions are longitude and latitude, and the third dimension is a meaningful physical index such as energy or time. We then introduce a novel multichannel deconvolution built upon the 2D-1D MS-VSTS, which allows us to get rid of both the noise and the blur introduced by the point spread function (PSF) in each energy (or time) band. The method is applied to simulated data from the Large Area Telescope (LAT), the main instrument of the Fermi Gamma-Ray Space Telescope, which detects high energy gamma-rays in a very wide energy range (from 20 MeV to more than 300 GeV), and whose PSF is strongly energy-dependent (from about 3.5° at 100 MeV to less than 0.1° at 10 GeV).
17 pages, 10 figures
References in corpus (3)
Cited by in corpus (8)
- The Denoised, Deconvolved, and Decomposed Fermi -ray sky - An application of the DPO algorithm
- Distinguishing Dark Matter from Unresolved Point Sources in the Inner Galaxy with Photon Statistics
- DPO - Denoising, Deconvolving, and Decomposing Photon Observations
- Second-Generation Curvelets on the Sphere
- A Simple Proposal for Radial 3D Needlets
- Wavelet-Based Segmentation on the Sphere
- Multi-Component Imaging of the Fermi Gamma-ray Sky in the Spatio-spectral Domain
- SNIa detection in the SNLS photometric analysis using Morphological Component Analysis