Image fusion based on median filters and SOFM neural networks: a three-step scheme
Signal Processing - Special section on information theoretic aspects of digital watermarking
Image Fusion Algorithm Using RBF Neural Networks
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Fuzzy image fusion based on modified Self-Generating Neural Network
Expert Systems with Applications: An International Journal
Fast photo time-stamp recognition based on SGNN
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
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Multi-sensor image fusion is a challenging research field, which is a issue to be further investigated and studied. Self-Generating Neural Networks (SGNNs) are self-organization neural network, whose network structures and parameters need not to be set by users, and its learning process needs no iteration. An approach of image fusion using a SGNN is proposed in this paper. The approach consists of pre-processing of the images, clustering pixels using SGNN and fusing images using fussy logic algorithms. The approach has advantages of being wieldy to be used by users and having high computing efficiency, The experimental results demonstrate that the MSE (mean square error) of this approach decreases 30%-60% than those by Laplacian pyramid and discrete wavelet transform approaches.