An High Equipped Image Reconstruction Framework Based on Morphologic Regularization approach Using Bregman Iteration SR algorithm

Prashant B. Raule, Ravindra P. Shelkikar

Abstract


Feature extractions are the novel techniques in image processing to store its unique characteristics. Morphological operators are the best for any image processing applications because it helps to preserve some characteristics from image. Although morphological operators is successful in solving the feature extraction but it too has some drawbacks. In this paper we model a non linear regularization method based on multi scale morphology for edge preserving super resolution (SR) image reconstruction. We formulate SR reconstruction problem from low resolution (LR) image as a deblurring and denoising and then solve the inverse problem using Bregman iterations. The proposed Method can be reduce inherent noise generated during low-resolution image formation as well as during SR image estimation efficiently. Using MATLAB simulation results we showed the effectiveness of the proposed method and reconstruction method for SR image.


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