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Single Image Super-Resolution using Back-Propagation Neural Networks

Haque, Salman Taseen and HASAN, Mohammad (2017) Single Image Super-Resolution using Back-Propagation Neural Networks. In: 20th International Conference on Computer and Information Technology (ICCIT 2017), 22 Dec 2017, Dhaka, Bangladesh.

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Abstract or description

There are several existing mathematical algorithms for colour image upscaling like Nearest Neighbour, Bicubic and Bilinear. This paper firstly investigates the performances of these three and it has been found that Bicubic performs the best in terms of structural similarity and execution time. A Bicubic with backpropagation based ANN method has been proposed to improve the results. Bicubic with ANN shows 6.5% higher SSIM, 6.9% higher PSNR, 8.7% higher SNR and 30.23% lower MSE values than pure Bicubic. The results of Bicubic with ANN are also compared with state of the art super-resolution techniques like SRCNN. Bicubic with ANN produces 1.48% higher SSIM and 3.44% higher PSNR than SRCNN.

Item Type: Conference or Workshop Item (Paper)
Faculty: School of Computing and Digital Technologies > Computing
Depositing User: Mohammad HASAN
Date Deposited: 13 Mar 2018 15:08
Last Modified: 16 Mar 2018 13:16

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