Certain Investigation on Hyper Spectral Remote Sensing Image

Authors

  • C. Rajinikanth  Research Scholar, Department of Electronics & Instrumentation Engineering, Annamalai University, India
  • Dr. S. Abraham Lincon  Professor, Department of Electronics & Instrumentation Engineering, Annamalai University, India

Keywords:

Hyper Spectral Remote Sensing Image, Image Classification

Abstract

In this paper, a technique has been designated for classification of satellite remote sensing of hyperspectral image. The classification process is based on the three main categories: (1) Clustering, which performed in supervised techniques using Thresholding effect of image pixel intensity and (2) segmented and texture based image analysis, in this process to achieve a new textural based image clustering to overcome the problem of multi-label images in satellite remote processing. Finally, it is clustered and result in segmented output.

References

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  2. Ribana Rosche, and Björn Waske, “Shapelet-Based Sparse Representation for Landcover Classification of Hyperspectral Images” IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(3),pp.1623-1634.
  3. Guiyun Zhou, Shuai Cao, and Junjie Zhou, “Planar Segmentation Using Range Images From Terrestrial Laser Scanning”, IEEE Geoscience And Remote Sensing Letters, 2016,13(2),pp.257-261.
  4. Yanfei Zhong, Rongrong Gao, and Liangpei Zhang,“Multiscale and Multifeature Normalized Cut Segmentation for High Spatial Resolution Remote Sensing Imagery” IEEE Transactions On Geoscience And Remote Sensing, 2016,54(10),pp.6061-6075.
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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-04-28

Issue

Volume 5, Issue 3, March-April-2018

Section

Research Articles

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Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
C. Rajinikanth, Dr. S. Abraham Lincon, " Certain Investigation on Hyper Spectral Remote Sensing Image, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 5, Issue 3, pp.129-131, March-April-2018.