Unsupervised classification of hyperspectral data: an ICA mixture model based approach-Reference-Cited by-同舟云学术

Unsupervised classification of hyperspectral data: an ICA mixture model based approach

Published:2004-01 Issue:2 Volume:25 Page:481-487
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Shah Chintan A.¹,Arora Manoj K.¹,Varshney Pramod K.¹

Affiliation:

1. a Department of Electrical Engineering and Computer Science , Syracuse University , Syracuse, NY 13 244, USA

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431160310001618040

Reference15 articles.

1. Chiang S. S Chang C. I 2000 Unsupervised hyperspectral image analysis using independent component analysisIEEE International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, USA, 24–28 July 2000(Piscataway, NJ: IEEE), 7, pp. 3136–3138

2. Independent component analysis, A new concept?

3. A review of assessing the accuracy of classifications of remotely sensed data

4. Duda R. O Hart P. E Stork D. G 2001Pattern Classification, 2nd edn (New York: John Wiley & Sons)

5. Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection approach

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