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
Total variation regularization has good performance in noise removal and edge preservation but lacks in texture restoration.Here we present a texture-preserving strategy to restore images contaminated by blur and nois...Total variation regularization has good performance in noise removal and edge preservation but lacks in texture restoration.Here we present a texture-preserving strategy to restore images contaminated by blur and noise.According to a texture detection strategy,we apply spatially adaptive fractional order diffusion.A fast algorithm based on the half-quadratic technique is used to minimize the resulting objective function.Numerical results show the effectiveness of our strategy.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.
基金This work has been partially supported by MIUR-Prin 2008,ex60%project by University of Bologna"Funds for selected research topics"and by GNCS-INDAM.
文摘Total variation regularization has good performance in noise removal and edge preservation but lacks in texture restoration.Here we present a texture-preserving strategy to restore images contaminated by blur and noise.According to a texture detection strategy,we apply spatially adaptive fractional order diffusion.A fast algorithm based on the half-quadratic technique is used to minimize the resulting objective function.Numerical results show the effectiveness of our strategy.
