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Super Resolution Image Reconstruction Through Bregman Iteration Using Morphologic Regularization

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2 Author(s)
Pulak Purkait ; Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India ; Bhabatosh Chanda

Multiscale morphological operators are studied extensively in the literature for image processing and feature extraction purposes. In this paper, we model a nonlinear regularization method based on multiscale morphology for edge-preserving super resolution (SR) image reconstruction. We formulate SR image reconstruction as a deblurring problem and then solve the inverse problem using Bregman iterations. The proposed algorithm can suppress inherent noise generated during low-resolution image formation as well as during SR image estimation efficiently. Experimental results show the effectiveness of the proposed regularization and reconstruction method for SR image.

Published in:

IEEE Transactions on Image Processing  (Volume:21 ,  Issue: 9 )