Super resolution image reconstruction through Bregman iteration using morphologic regularization.
basic_science · Level V
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- Record sourced from PubMed, PMID 22652193.
- Also identified by DOI 10.1109/TIP.2012.2201492.
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Abstract
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.