Date of Publication :8th March 2017

Abstract: The objective of this paper is to estimate a high resolution medical image from a single noisy low resolution image with the help of given database ofhigh and low resolution image patch pairs. Initially a total variation (TV)method which helps in removing noise effectively while preserving edgeinformation is adopted. Further de-noising and super resolution is performedon every image patch. For each TV denoised low-resolution patch, its high-resolution version is estimated based on finding a nonnegative sparse linearrepresentation of the TV denoised patch over the low-resolution patches fromthe database, where the coefficients of the representation strongly depend onthe similarity between the TV denoised patch and the sample patches in thedatabase. The problem of finding the nonnegative sparse linear representationis modeled as a nonnegative quadratic programming problem. The proposedmethod is especially useful for the case of noise-corrupted and low-resolutionimage.

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