SEGMENTATION-BASED MULTIFRAME BLIND DECONVOLUTION OF SOLAR IMAGES

A blind deconvolution method is applied to the recovery of atmospherically degraded solar images. The method consists of an iterative deconvolution algorithm that uses several partial images segmented from each of multiple frames. It is shown that the algorithm decreases a specified error metric, allows a unique solution, and reduces contamination originally existing in solar images observed with a limited field of view. Artificial contamination introduced into the partial images by segmentation is calibrated with the use of estimates of an object and a point-spread function at the previous iteration. Computer simulation demonstrates successful reconstruction for a low-contrast degraded image and the expected behavior of an error metric. High-resolution images are reconstructed from observed solar images.