Year: 2002
Type: article
Abstract: This article reviews different deconvolution methods. The all‐pervasive presence of noise is what makes deconvolution particularly difficult. The diversity of resulting algorithms reflects different ways of estimating the true signal under various idealizations of its properties. Different ways of approaching signal recovery are based on different instrumental noise models, whether the astronomical objects are pointlike or extended, and indeed on the computational resources available to the analyst. We present a number of recent results in this survey of signal restoration, including in the areas of superresolution and dithering. In particular, we show that most recent published work has consisted of incorporating some form of multiresolution in the deconvolution process.
DOI: 10.1086/342606
Authors: J. L. Starck, E. Pantin, F. Murtagh
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2011687187