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Comparative Study of Algorithms for Hyper Spectral Image Classification

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  • Pallavi Juyal
  • Manish Jain
  • Varsha Nemade

Abstract

Now days the use of remote sensing imagery has increased drastically, ranging from the applications in farms to that in the field of defense. These images range from hyper spectral, multispectral to ultra spectral. One of the major applications of the remote sensing image is that of classification of the image. Several algorithms have been found for classification of images based on various factors [4]. The algorithms used for classification are either supervised or unsupervised. In this paper we study different algorithms used for classification of the hyper spectral images. An analysis of the output obtained by the implementation of various algorithms has also been done. The analysis has been done based on the number of pixels classified.

Suggested Citation

  • Pallavi Juyal & Manish Jain & Varsha Nemade, 2017. "Comparative Study of Algorithms for Hyper Spectral Image Classification," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(2), pages 1000-1004, April.
    • Handle: RePEc:jbh:ijsrcs:v2:y2017:i2:id:hcseit1722312
    Note: Article URL: https://ijsrcseit.com/CSEIT1722312
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