@inproceedings{d7620abfc6d74a76b27aa27781ffe1d6,
title = "Dimension reduction for hyperspectral image based on the second generation bandelet transform",
abstract = "A dimensionality reduction method is proposed by using the second generation Bandelet transform. The redundant components of the hyperspectral cube are firstly partitioned into several subsets. Subsequently the Bandelet coefficients and the geometries flows of the hyperspectral image are generated by performing second generation Bandelet transform. In the follow step, Principal Components Analysis (PCA) is introduced to simplify the redundant data. Finally, the new reduced hyperspectral cube is reconstructed by taking inverse Bandelet transform. Some numerical simulations are made to test the validity and capability of the proposed dimensionality reduction algorithm.",
keywords = "Bandelet transform, Dimensionality reduction, Hyperspectral, Mutipscale",
author = "Xiaoping Du and Hang Chen and Zhengjun Liu and Ming Liu and Xiangzhen Cheng",
year = "2013",
doi = "10.1117/12.2032800",
language = "英语",
isbn = "9780819497796",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
booktitle = "International Symposium on Photoelectronic Detection and Imaging 2013",
address = "美国",
note = "5th International Symposium on Photoelectronic Detection and Imaging, ISPDI 2013 ; Conference date: 25-06-2013 Through 27-06-2013",
}