Minimizing Aliasing Effects Using Faster Super Resolution Technique on Text Images
Image quality improvement is not bounded within the application of different types of filtering. Resolution improvement is also essential and it solely depends on the estimation of the unknown pixel value that involves a lot of computation. Here a resolution enhancement technique is proposed to reduce the aliasing effects from the text documented image with a reduced amount of computational time. The proposed hybrid method provides better resolution at most informative regions. Here, the unknown pixel value is estimated based on their local informative region. This technique finds the most informative areas, discontinuity at the edges and less informative areas separately. The foreground regions are segmented at the first phase. The unknown pixels values of the foreground regions are calculated in the second step. All-of-these separated images are combined together to construct the high-resolution image at the third phase. The proposed method is mainly verified on aliasing affected text documented images. A distinct advantage of the proposed method over other conventional approaches is that it requires lower computational time to construct a high-resolution image from a single low-resolution one.
KeywordsSingle image super resolution Aliasing Clustering K nearest neighbour Feature similarity index metrics
I would like to acknowledge Visvesvaraya PhD Scheme for Electronics and IT. I am also thankful to Department of Computer Science and Engineering, University of Calcutta for infrastructural supports.
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