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<article xlink="http://www.w3.org/1999/xlink" dtd-version="1.0" article-type="general-sciences" lang="en"><front><journal-meta><journal-id journal-id-type="publisher">IJCRR</journal-id><journal-id journal-id-type="nlm-ta">I Journ Cur Res Re</journal-id><journal-title-group><journal-title>International Journal of Current Research and Review</journal-title><abbrev-journal-title abbrev-type="pubmed">I Journ Cur Res Re</abbrev-journal-title></journal-title-group><issn pub-type="ppub">2231-2196</issn><issn pub-type="opub">0975-5241</issn><publisher><publisher-name>Radiance Research Academy</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">1638</article-id><article-id pub-id-type="doi">10.7324/IJCRR.2017.9131</article-id><article-id pub-id-type="doi-url"/><article-categories><subj-group subj-group-type="heading"><subject>General Sciences</subject></subj-group></article-categories><title-group><article-title>Graphical Processing Unit Accelerated Face Resolution Enhancement using Pixels - Homogeneity and Relative- Ratios&#13;
</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Mutneja</surname><given-names>Vikram</given-names></name></contrib><contrib contrib-type="author"><name><surname>Singh</surname><given-names>Satvir</given-names></name></contrib></contrib-group><pub-date pub-type="ppub"><day>3</day><month>07</month><year>2017</year></pub-date><volume>)</volume><issue/><fpage>1</fpage><lpage>5</lpage><permissions><copyright-statement>This article is copyright of Popeye Publishing, 2009</copyright-statement><copyright-year>2009</copyright-year><license license-type="open-access" href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made.</license-p></license></permissions><abstract><p>This work presents a GPU (Graphical Processing Unit) accelerated spatial domain oriented face resolution enhancement algorithm based on the homogeneity levels and relative-ratios of the pixels with respect to its surrounding pixels. The algorithm has been developed, implemented as well as tested in the MATLAB environment. MATLAB is slow in processing but at the same time a resourceful environment for the development in the area of image processing owing to its extremely rich set of functions and programmer-friendly integrated development environment. However, to compensate for the speed loss in testing and implementation phase, we have made use of GPU computing i.e. done parallelization of the algorithm on NVIDIA GPU using CUDA (Compute Unified Device Architecture) interface in the MATLAB environment. It is a simple but efficient algorithm in which kernel matrices are created encoding the homogeneity levels and relative-ratios of all pixels in surrounding four quadrants. Kernel matrices are subsequently applied to reconstruct the HR (High-Resolution) version from input LR (Low-Resolution) facial image.&#13;
</p></abstract><kwd-group><kwd>Image processing</kwd><kwd> GPU computing</kwd><kwd> Face resolution enhancement</kwd><kwd> Surveillance videos</kwd><kwd> Spatial domain processing</kwd></kwd-group></article-meta></front></article>
