Maximum-entropy image processing in gamma-ray astronomy.

Abstract

In order to make the fullest use of the information contained in data from a spark-chamber telescope, an image processing approach, is required. It is shown how the maximum-entropy reconstruction technique can be applied in a modification appropriate to a situation of low statistical weight per resolution solid angle, as usually occurs with present instruments observing the gamma-ray sky. The final decision relating to the choice of map can be made by using the Kolmogoroff-Smirnoff nonparametric test. Properties of the algorithm are investigated by using simulated data, and a degree of superresolution is found possible even with quite poor statistics. Some examples of an application to data from the COS B satellite are presented to show the power of the method.