Landsat PNN classifier using PCA of wavelet texture-edge feature

Harold H. Szu; Jacqueline Le Moigne; N. S. Netanyahu; Charles C. Hsu

Landsat PNN classifier using PCA of wavelet texture-edge feature

Harold H. Szu, Jacqueline Le Moigne, N. S. Netanyahu, Charles C. Hsu

Naval Surface Warfare Center

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

This work focuses on neural network classifiers on sub-regions of the image. Texture information obtained with a wavelet transform is integrated in such a classifier for purposes of improving its performance. Using a wavelet transform, statistical texture information in Landsat/TM imagery is accounted. Statistical texture is extracted with a continuous edge-texture composite wavelet transform. Finally, the network is trained with both the texture information and the additional pixel labels provided by the ground truth data.

Original language	English
Pages (from-to)	141-153
Number of pages	13
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	3723
State	Published - 1999
Externally published	Yes

Cite this

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abstract = "This work focuses on neural network classifiers on sub-regions of the image. Texture information obtained with a wavelet transform is integrated in such a classifier for purposes of improving its performance. Using a wavelet transform, statistical texture information in Landsat/TM imagery is accounted. Statistical texture is extracted with a continuous edge-texture composite wavelet transform. Finally, the network is trained with both the texture information and the additional pixel labels provided by the ground truth data.",

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AB - This work focuses on neural network classifiers on sub-regions of the image. Texture information obtained with a wavelet transform is integrated in such a classifier for purposes of improving its performance. Using a wavelet transform, statistical texture information in Landsat/TM imagery is accounted. Statistical texture is extracted with a continuous edge-texture composite wavelet transform. Finally, the network is trained with both the texture information and the additional pixel labels provided by the ground truth data.

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Landsat PNN classifier using PCA of wavelet texture-edge feature

Abstract

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