Abstract
In this paper we present a Gabor Wavelet Network, a wavelet neural network based on Gabor functions, applied to image registration. Although wavelet network is time consuming technique, we decrease computational costs by incorporating three techniques: gradient-based feature selection, Gabor filtering, and wavelet neural network. Similarity criterion is built upon analyzing intensity function with Gabor Wavelet Network, which carries out the image registration by both gradient-based and texture features.
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© 2006 Springer-Verlag Berlin Heidelberg
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Spinko, V., Shi, D., Ng, W.S., Leong, JL. (2006). Gabor Neural Network for Endoscopic Image Registration. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_70
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DOI: https://doi.org/10.1007/11760023_70
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34437-7
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