Image Super Resolution Using Back-Projection based on Canny Edge Detection and Gabor Filter Prior
DOI:
https://doi.org/10.37591/joipprp.v2i3.484Keywords:
Super resolution, iterative back-projection, projection onto convex sets, mean square error, peak signal to noise ratio, mean absolute errorAbstract
In recent years, due to the advancement of mixed media instrumentation and machine gadgets, single-image super resolution has currently been converted into a thought subject. Super-resolution is the procedure of improving a high-resolution image from varied low-resolution pictures of a similar scene. The key goal of super-resolution imaging is to reproduce a higher-resolution image focused around a group of pictures, procured from a similar scene and indicated as “low-resolution” pictures, to beat the confinement and/or not well postured states of the image securing methodology for encouraging higher substance visualization and scene distinguishment. Super resolution of the image is model as a backwards issue, that's the target of super resolution is to invert the impact of the down sampling, obscuring and twisting that relate the LR image to imaginary time unit image. The repetitive back-projection is a long time super-resolution strategy with low process many-sided quality which will be connected continuously applications. The methodology is focused around associate an iterative back-projection technique joined with the canny edge detection and Gabor filter prior.
Cite this Article
Prachi Patel, Swadas Prashant B, Jaliya Udesang K. Image Super Resolution Using Back-Projection based on Canny Edge Detection and Gabor Filter Prior. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(3): 48–56p.
References
Bareja Milan N, Modi Chintan K. An Effective Iterative Back Projection based Single Image Super Resolution Approach. 2012 International Conference on Communication Systems and Network Technologies, IEEE.
Shen-Chuan Tai, Tse-Ming Kuo, Chon-Hong Iao, et al. A Fast Algorithm for Single-Image Super Resolution in both Wavelet and Spatial Domain. Image Processing, 2012 International Symposium on Computer, Consumer and Control, IEEE.
Pradeep Sen, Soheil Darabi. Compressive Image Super-Resolution. IEEE. 2009.
Makwana Rujul R, Mehta Nita D. Survey On Single Image Super Resolution Techniques. International Journal of Electronics and Communication Engineering (IOSR-JECE). Mar–Apr 2013; 5(5).
Liyakathunisa, Ravi Kumar CN, Ananthashayana VK. Super Resolution Reconstruction of Compressed Low Resolution Images using Wavelet Lifting Schemes. 2009 Second International Conference on Computer and Electrical Engineering, IEEE.
SapanNaik, Nikunj Patel. Single Image Super Resolution in Spatial and Wavelet Domain. The International Journal of Multimedia & Its Applications (IJMA). Aug 2013; 5(4).
Kaibing Zhang, Xinbo Gao., Dacheng Tao, et al. Single Image Super-Resolution with Multiscale Similarity Learning. IEEE Trans Neural Netw Learn Syst. Oct 2013; 24(10).
Patel Shreyas, Baxi Aatha. Single Image Super Resolution. International Journal of Engineering Research & Technology (IJERT). Dec 2012; 1(10).
Manoj KY, Venkatesh UC, Antony PJ. A Super-Resolution Based Image in Painting in the Advertence of Exemplar Technique. International Journal of Engineering Research & Technology (IJERT). Apr 2013; 3(4).
Krunal Shah, Jaymit Pandya, Safvan Vahora. A Survey on Super Resolution Image Reconstruction Techniques. International Journal of Engineering Research & Technology (IJERT). Apr 2013; 2(4).
Sudheer Babu R, Sreenivasa Murthy KE. A Survey on the Methods of Super-Resolution Image Reconstruction. International Journal of Computer Applications (IJCA). Feb 2011; 15(2).
Brian Leung, Seda Ogrenci Memik. Exploring Super-Resolution Implemen-tations across Multiple Platforms. EURASIP J Adv Signal Process, Springer. 2013.
Niyanta Panchal, Bhailal Limbasiya, Ankit Prajapati. Survey on Multi-Frame Image Super Resolution. International Journal of Scientific & Technology Research (IJSTR). Nov 2013; 2(11).
Russell Hardie. A Fast Image Super-Resolution Algorithm Using an Adaptive Wiener Filter. IEEE Trans Image Process. Dec 2007; 16(12).
Prachi Patel, Prashant Swadas, Udesang Jaliya. A Survey on Image Super Resolution Techniques. International Journal of Innovative and Emerging Research in Engineering (IJIERE). Feb 2015; 2(1): 84–89p. e-ISSN: 2394-3343.
Baikun Wan, Lin Meng, Dong Ming, et al. Video Image Super-resolution Restoration Based on Iterative Back-Projection Algorithm. CIMSA 2009-International Conference on Computational Intelligence for Measurement Systems and Applications, IEEE.
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