New image super-resolution scheme based on residual error restoration by neural networks

Fengzhi Pan; Liming Zhang

doi:10.1117/1.1604397

1 October 2003 New image super-resolution scheme based on residual error restoration by neural networks

Fengzhi Pan, Liming Zhang

Optical Engineering, Vol. 42, Issue 10, (October 2003). https://doi.org/10.1117/1.1604397

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.

©(2003) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Fengzhi Pan and Liming Zhang "New image super-resolution scheme based on residual error restoration by neural networks," Optical Engineering 42(10), (1 October 2003). https://doi.org/10.1117/1.1604397

Published: 1 October 2003

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