Abstract
Aiming at the characteristics of remote sensing image classification, the mixed pixel problem is one of the main factors that affect the improvement of classification precision in remote sensing classification. In this paper ,A tray neural network model was established to solve the mixed pixel classification problems. ETM+ data of DaLi in May 2001 is selected in the study. The results show that this method effectively solves mixed pixel classification problem, improves network learning speed and classification accuracy, so it is one kind of effective remote sensing imagery classifying method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Pawlak, Z.: Rough sets. International Journal of Computer and Information Sciences 11, 341–356 (1982)
Simpson, J.J., Mcintir, J.T.: A recurrent neural network classifier for improved retrievals of areal extent of snow cover. IEEE Transaction on Geoscience and Remote Sensing 39(10), 2135–2147 (2001)
Hasi, B., Ma, J., Li, Q., et al.: The self-organizingfeature map neural networks classification of the ASTER Data based on wavelet Fusion. Science in China, Series D 47(7), 651–658 (2004)
Daijin, K.: Data classification based on tolerant rough set. Pattern Recognition 34, 1613–1624 (2001)
Hasi, B., Ma, J., Zhou, Z.: Study on the artificial neural network method used for weather and AVHRR Thermal Data Classification. Journal of The Graduate School of The Chinese Academy of Sciences 20(3), 328–333 (2003)
Adams, J.B., Sabol, D.E., Kapos, V., Filho, R.A., Roberts, D.A., Smith, M.O., Gillespie, A.R.: Classification of multi-spectral images based on fractions of end members: Application to land-cover change in the Brazilian Amazon. Remote Sensing of Environment
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, Z., Hu, G., Yao, S. (2007). Decomposition Mixed Pixel of Remote Sensing Image Based on Tray Neural Network Model. In: Kang, L., Liu, Y., Zeng, S. (eds) Advances in Computation and Intelligence. ISICA 2007. Lecture Notes in Computer Science, vol 4683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74581-5_33
Download citation
DOI: https://doi.org/10.1007/978-3-540-74581-5_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74580-8
Online ISBN: 978-3-540-74581-5
eBook Packages: Computer ScienceComputer Science (R0)