DocumentCode :
3113310
Title :
Hyperspectral Image Classification Methods in Remote Sensing - A Review
Author :
Sabale, Savita P. ; Jadhav, Chhaya R.
Author_Institution :
Pd. Dr. D. Y. Patil Inst. of Eng. & Technol., Savitribai Phule Pune Univ., Pune, India
fYear :
2015
fDate :
26-27 Feb. 2015
Firstpage :
679
Lastpage :
683
Abstract :
Hyper spectral image processing is becoming an active topic in remote sensing and other applications in current times. Hyper spectral images can easily distinguish materials which are spectrally similar. Many techniques are available to classify hyper spectral images which are mainly deals with the curse of dimensionality and working with few training data issues which confront during classification. This paper gives current approaches for classifying hyper spectral images based on supervised, unsupervised and semi supervised classification methods. This paper also discusses issues and prospect to conduct hyper spectral image classification to acquire good classification results.
Keywords :
geophysical image processing; image classification; remote sensing; hyperspectral image classification methods; image processing; remote sensing; semisupervised classification methods; supervised classification methods; unsupervised classification methods; Feature extraction; Hyperspectral imaging; Image classification; Shape; Training; Hyperspectral image classification; the high dimensionality of spectral channels; working with lack of labels;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing Communication Control and Automation (ICCUBEA), 2015 International Conference on
Conference_Location :
Pune
Type :
conf
DOI :
10.1109/ICCUBEA.2015.139
Filename :
7155934
Link To Document :
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