Image processing with the random neural network

Erol Gelenbe; Hakan Bakircioglu; Taskin Kocak

doi:10.1117/12.304658

1 April 1998 Image processing with the random neural network

Erol Gelenbe, Hakan Bakircioglu, Taskin Kocak

Proceedings Volume 3307, Applications of Artificial Neural Networks in Image Processing III; (1998) https://doi.org/10.1117/12.304658
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

Enhancing image quality and combining observations into a coherent description are essential tools in various image processing applications such as multimedia publishing, target recognition, and medical imaging. In this paper we propose two novel approaches for image enlargement and image fusion using the Random Neural Network (RNN) model, which has already been successfully applied to the problems such as still and moving image compression, and image segmentation. The advantage of the RNN model is that it is closer to biophysical reality and mathematically more tractable than standard neural methods, especially when used as a recurrent structure.

Citation Download Citation

Erol Gelenbe, Hakan Bakircioglu, and Taskin Kocak "Image processing with the random neural network", Proc. SPIE 3307, Applications of Artificial Neural Networks in Image Processing III, (1 April 1998); https://doi.org/10.1117/12.304658

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