Supervised, Unsupervised, and Semisupervised Classification Methods for Hyperspectral Image Classification-A Review
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064



Review Papers | Computer Science & Engineering | India | Volume 3 Issue 12, December 2014

Supervised, Unsupervised, and Semisupervised Classification Methods for Hyperspectral Image Classification-A Review

Savita P. Sabale, Asst. Prof. Chhaya R. Jadhav

Remote sensing involves collection and interpretation of information about an object, area or event without any physical contact with the object. All earth surfaces features which include minerals, vegetation, dry soil, water and snow have unique spectral reflectance signatures. These spectral signatures vary over the range of wavelengths in the electromagnetic spectrum and these all large number of signatures is correctly identified with hyperspectral images. Accurate classification of hyperspectral image is an evolving field in now days. In this section we give a wide outline of existing methodologies focused around supervised, unsupervised and semi-supervised hyperspectal image classification methods and some well known applications of hypergraph

Keywords: High Dimensionality, Lack of Training Samples, Supervised Classification Method, Unsupervised Classification Method, Semisupervised Classification Method, Applications of Hypergraph

Edition: Volume 3 Issue 12, December 2014

Pages: 256 - 260

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How to Cite this Article?

Savita P. Sabale, Asst. Prof. Chhaya R. Jadhav, "Supervised, Unsupervised, and Semisupervised Classification Methods for Hyperspectral Image Classification-A Review", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SUB14368, Volume 3 Issue 12, December 2014, 256 - 260

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