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Image Super Resolution Using Back-Projection based on Canny Edge Detection and Gabor Filter Prior

Prachi Patel, Prashant B Swadas, Udesang K Jaliya

Abstract


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.


Keywords


Super resolution, iterative back-projection, projection onto convex sets, mean square error, peak signal to noise ratio, mean absolute error

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References


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