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19 December 2002 Deconvolution of astronomical data: what for and where do we go?
Abstract
Modern astronomy tries to push the observation instruments to their limits in order to discover new unsuspected phenomena in the universe. However, some intrinsic limitations (diffraction or atmospheric seeing etc ...) that degrade strongly the spatial resolution when imaging objects in the sky, and can be hardly reduced simply by technology improvements. In order to get the best scientific return from new, more and more sensitive instruments, image deconvolution methods try to push back these limits. Indeed, when the spatial degradation is known, partly known, or even unknown, deconvolution algorithms have proven to be able to restore an original image that is close, within the errors of the method, to a perfect image as observed by a perfect instrument with no, or heavily reduced image degradation. Many methods and algorithms exist nowadays to solve numerically the problem of image deconvolution. I will review the most popular ones and show their characteristics and limitations. In particular, I will show how we moved from standard methods (which see the images as one unique object) to multiscale methods that analyse the data from a multiresolution point a view, decoupling an originally very complicated problem into a set of problems more easy to solve.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eric Pantin "Deconvolution of astronomical data: what for and where do we go?", Proc. SPIE 4847, Astronomical Data Analysis II, (19 December 2002); https://doi.org/10.1117/12.461973
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