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Artificial Neural Networks for Single-Image Super-Resolution

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 122 - Number 16
Year of Publication: 2015
Authors:
Gagandeep Singh
Gulshan Goyal
10.5120/21786-5075

Gagandeep Singh and Gulshan Goyal. Article: Artificial Neural Networks for Single-Image Super-Resolution. International Journal of Computer Applications 122(16):23-27, July 2015. Full text available. BibTeX

@article{key:article,
	author = {Gagandeep Singh and Gulshan Goyal},
	title = {Article: Artificial Neural Networks for Single-Image Super-Resolution},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {122},
	number = {16},
	pages = {23-27},
	month = {July},
	note = {Full text available}
}

Abstract

Image upscaling is an important field of digital image processing. It is often required to create higher resolution images from the lower resolution images at hand in computer graphics, media devices, satellite imagery etc. Upscaling is also referred to as 'single image super-resolution'. The process is a tradeoff between efficiency, time and the quality of output images obtained . In present paper, a feed forward neural network using supervised training for image upscaling is proposed. The performance of neural network is compared to bicubic interpolation method in terms of PSNR and MSE.

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