Super-resolution using sub-band constrained total variation

Authors:
Priyam Chatterjee;Vinay P. Namboodiri;Subhasis Chaudhuri
Affiliations:
University of California, Santa Cruz, California;Indian Institute of Technology, Powai, Bombay, Mumbai, India;Indian Institute of Technology, Powai, Bombay, Mumbai, India
Venue:
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Year:
2007

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Abstract

Super-resolution of a single image is a severely ill-posed problem in computer vision. It is possible to consider solving this problem by considering a total variation based regularization framework. The choice of total variation based regularization helps in formulating an edge preserving scheme for super-resolution. However, this scheme tends to result in a piece-wise constant resultant image. To address this issue, we extend the formulation by incorporating an appropriate sub-band constraint which ensures the preservation of textural details in trade off with noise present in the observation. The proposed framework is extensively evaluated and the experimental results for the same are presented.