DECONVOLUTION OF ASTRONOMICAL IMAGES USING THE MULTISCALE MAXIMUM-ENTROPY METHOD

Following the ideas of Bontekoe et al. who noticed that the classical Maximum Entropy Method (MEM) had difficulties to efficiently restore h igh and low spatial frequency structure in an image at the same time, we use the wavelet transform, a mathematical tool to decompose a signa l into different frequency bands. We introduce the concept of multi-sc ale entropy of an image, leading to a better restoration at all spatia l frequencies. This deconvolution method is flux conservative and the use of a multiresolution support solves the problem of MEM to choose t he a parameter, i.e. the relative weight between the goodness-of-fit a nd the entropy. We show that our algorithm is efficient too for filter ing astronomical images. A range of practical examples illustrate this approach.