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Optical Engineering

New image super-resolution scheme based on residual error restoration by neural networks
Author(s): Fengzhi Pan; Liming Zhang
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Paper Abstract

The scheme proposed combines an existing image interpolation algorithm with an artificial neural network (ANN) used to model the residual errors between the interpolated image and the respective original image. Mathematical analysis shows that the performance of the proposed method is superior to that of known single-frame interpolation algorithms. The image restoration results using the presented scheme indicate that the restored images are very similar to the real high-resolution images. We also illustrate that the performance of any single-frame interpolation algorithm can be enhanced by combining the interpolation algorithm into our scheme. Experimental results show the proposed method on generalization and computation complexity is superior to other neural network schemes.

Paper Details

Date Published: 1 October 2003
PDF: 9 pages
Opt. Eng. 42(10) doi: 10.1117/1.1604397
Published in: Optical Engineering Volume 42, Issue 10
Show Author Affiliations
Fengzhi Pan, Fudan Univ. (China)
Liming Zhang, Fudan Univ. (China)


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