Improving restoration of microscopy images using iterative prototypes and a sequence of support constraints

Images obtained by wide-field microscopy are specially corrupted by an out-of-focus blur on the axial direction. Constrained restoration algorithms are able to restore some of the frequencies lost on the acquisition process by using prior knowledge. We report an improved restoration algorithm using prototype images produced by the iterative Richardson-Lucy algorithm and a sequence of finite support constraint sets. The finite support shrinks as the nonlinear restoration is performed. Results showed an improved restoration on images with dense background, achieving a larger passband and restoration on axial direction. It encourages the development of new restoration algorithms based on the projection onto sequence of sets.