Image deconvolution problems with a symmetric point-spread function arisein many areas of science and engineering. These problems often are solved by theRichardson-Lucy method, a nonlinear iterative method. We first s...Image deconvolution problems with a symmetric point-spread function arisein many areas of science and engineering. These problems often are solved by theRichardson-Lucy method, a nonlinear iterative method. We first show a convergenceresult for the Richardson-Lucy method. The proof sheds light on why the method mayconverge slowly. Subsequently, we describe an iterative active set method that imposesthe same constraints on the computed solution as the Richardson-Lucy method. Computed examples show the latter method to yield better restorations than the RichardsonLucy method and typically require less computational effort.展开更多
基金We would like to thank the referees for comments.This work was supported by PRIN-MIUR-Cofin 2008 project,GNCS-INDAM,an OBR Research Challenge Grant,and NSF grant DMS-1115385.
文摘Image deconvolution problems with a symmetric point-spread function arisein many areas of science and engineering. These problems often are solved by theRichardson-Lucy method, a nonlinear iterative method. We first show a convergenceresult for the Richardson-Lucy method. The proof sheds light on why the method mayconverge slowly. Subsequently, we describe an iterative active set method that imposesthe same constraints on the computed solution as the Richardson-Lucy method. Computed examples show the latter method to yield better restorations than the RichardsonLucy method and typically require less computational effort.
