PROJECT TITLE :
Wavelet-Based Single Image Super-Resolution With An Overall Enhancement Procedure - 2017
In this paper, we have a tendency to address the problem of generating an excellent-resolution image primarily based on a dictionary of low- and high-resolution exemplars from a single input image in wavelet domain with a overall enhancement procedure. Most methods extract different kinds of features in low-resolution image and high-resolution images to establish the mapping relation. But in this paper, we have a tendency to implement wavelet-rework to extract the same reasonably feature to form the mapping more affordable. Meanwhile we have a tendency to implement native Lipschitz regularity constraint and structure-keeping constraint to preserve the native singularity and edge in our methodology. Compared with current state-of-art strategies on customary pictures, our technique obtains each visual and PSNR improvement.
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