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Original Articles

A new approach for spectral feature extraction and for unsupervised classification of hyperspectral data based on the Gaussian mixture model

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Pages 123-167 | Published online: 19 Oct 2009

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Woojin Doo & Heeyoung Kim. (2022) Simultaneous band selection and segmentation of hyperspectral images via a mixture of finite maximum margin mixtures. International Journal of Remote Sensing 43:6, pages 2296-2314.
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D. Lu & Q. Weng. (2007) A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing 28:5, pages 823-870.
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A. Koltunov, O. Crouvi & E. Ben‐Dor. (2006) Geomorphologic mapping from hyperspectral data, using Gaussian mixtures and lower confidence bounds. International Journal of Remote Sensing 27:20, pages 4545-4566.
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A. Koltunov$suffix/text()$suffix/text() & E. Ben-Dor. (2004) Mixture density separation as a tool for high-quality interpretation of multi-source remote sensing data and related issues . International Journal of Remote Sensing 25:16, pages 3275-3299.
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Articles from other publishers (3)

Qing Yan, Yun Ding, Jing-Jing Zhang, Yi Xia & Chun-Hou Zheng. (2019) A discriminated similarity matrix construction based on sparse subspace clustering algorithm for hyperspectral imagery. Cognitive Systems Research 53, pages 98-110.
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D Chutia, D K Bhattacharyya, K K Sarma, R Kalita & S Sudhakar. (2016) Hyperspectral Remote Sensing Classifications: A Perspective Survey. Transactions in GIS 20:4, pages 463-490.
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Haihui Wang, Junhua Zhang, Kai Xiang & Yang Liu. (2009) Classification of Remote Sensing Agricultural Image by Using Artificial Neural Network. Classification of Remote Sensing Agricultural Image by Using Artificial Neural Network.

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