6 December 2002 MLP neural network super-resolution restoration for the undersampled low-resolution image
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Abstract
It is difficult to achieve restoration of high frequency information by the traditional algorithms using an undersampled and degraded low-resolution image. Nonlinear algorithms provide a better solution to above problem. As a nonlinear and real-time processing method, a MLP neural network super-resolution restoration for the undersampled and degraded low-resolution image is proposed. Experimental results demonstrate that the proposed approach can achieve super-resolution and a good restored image.
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Binghua Su, Binghua Su, Weiqi Jin, Weiqi Jin, LiHong Niu, LiHong Niu, Guangrong Liu, Guangrong Liu, "MLP neural network super-resolution restoration for the undersampled low-resolution image", Proc. SPIE 4787, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation V, (6 December 2002); doi: 10.1117/12.452494; https://doi.org/10.1117/12.452494
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