Abstract
Using ridgelet transform to do the feature extraction, and RBFNN to do the recognition and classification, a remote sensing image recognition method is put forward in this paper. We do mathematical implementation and experimental investigation of ridgelet transform to analyze its characteristic and show its performance. Since ridgelet transform outperforms wavelet transform in extracting the linear features of objects, the proposed method has higher efficiency than that of wavelets. The simulation in remote sensing image shows its feasibility..
This work was supported by the National Science Foundation under grant no. 60133010.
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© 2006 Birkhäuser Verlag Basel/Switzerland
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Ren, Y., Wang, S., Yang, S., Jiao, L. (2006). Ridgelet Transform as a Feature Extraction Method in Remote Sensing Image Recognition. In: Qian, T., Vai, M.I., Xu, Y. (eds) Wavelet Analysis and Applications. Applied and Numerical Harmonic Analysis. Birkhäuser Basel. https://doi.org/10.1007/978-3-7643-7778-6_38
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DOI: https://doi.org/10.1007/978-3-7643-7778-6_38
Publisher Name: Birkhäuser Basel
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