期刊
IEEE TRANSACTIONS ON IMAGE PROCESSING
卷 21, 期 9, 页码 4029-4039出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2012.2201492
关键词
Bregman iteration; deblurring; morphologic regularization; operator splitting; subgradients
资金
- DST, GOI under the Indian Digital Heritage-Hampi Project
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.
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