An Adaptive Image Regularization Technique for Image Deblurring
Mrinal Anand · International Journal for Research in Applied Science and Engineering Technology · 2020
Image processing is important on various fields to achieve various functions. In this paper two classes of regularization strategies to achieve image recovery and reduce noise suppression from Original image in projection-based image deblurring. Landweber iteration leads to a fixed level of regularization, which allows us to achieve fine-granularity control of projection-based iterative deblurring by varying the value. Regularization filters can be gained by probing into their asymptotic behavior-the fixed point of nonexpansive mappings. Different image structures (smooth regions, regular edges and textures) are observed correspond to different fixed points of nonexpansive mappings when the temperature (regularization) parameter varies. Such an analogy motivates us to propose a deterministic annealing based approach toward spatial adaptation in projection-based image deblurring.