An Improved Image Super Resolution and Its Parallel Implementation Based on CUDA
Chenyan Feng1, Xiaoyun Zhang2, Zhiyong Gao3
Journal of Multimedia Processing and Technologies, Vol. 6, No. 3, 2015.
DOI: 
Link: http://www.dline.info/jmpt/fulltext/v6n3/v6n3_3.pdf
Abstract:
Image super resolution (SR) based on self-similarity has achieved impressive results by exploiting the local
similarity across various scaled images. However, it is time consuming and far from meeting practical applicationsâ€™ requirements
and it is prone to unnatural visual artifacts such as facets and enhanced noise. In this paper, with the powerful general
purpose GPU, an accelerated parallel implementation based on NVIDIA CUDA architecture has been proposed. Then
denoising is combined and implemented together during the SR processing using the patch matching information of similarity,
and it makes the images clearer and cleaner. Also, subpixel accuracy of interpolation and searching is applied to improve the
similarity matching process, which make the upscaled images more natural-looking. Experimental results demonstrate that
the proposed method achieves an impressive speedup rate and produces improved visual quality images in comparison with
other state-of-the-art SR.