<title>Space-variant point-spread-function deconvolution of Hubble imagery using the Connection Machine</title>

Abstract

The spherical aberration errors which are present in the Hubble Space Telescope optical system produce a space variant point spread function where only 20% of the photons are concentrated in an area corresponding to the diffraction limit of the telescope. Deconvolution techniques can be used to concentrate the remaining 80% of the photons into the Airy core of the images thus restoring diffraction limited performance. Since the point spread function is space variant the normal Fourier transform convolution techniques are difficult to implement. We have developed an image space based convolution routine on the Connection Machine which can be used with a variety of deconvolution algorithms. The space variant point spread function is approximated by assuming isoplanatic patches in the image which can vary in size from 2 X 2 to 32 X 32 pixels. We present timing examples of two popular deconvolution techniques: the Maximum Entropy Method and the Richardson-Lucy method. Thirty iterations of either algorithm on a 512 X 512 image using 256 different point spread functions is accomplished in 90 seconds.