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A Survey on Trends and Techniques used in Hyperspectral Image Processing

by Sonia Sarmah, Sanjib Kr. Kalita
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 9
Year of Publication: 2015
Authors: Sonia Sarmah, Sanjib Kr. Kalita
10.5120/21725-4879

Sonia Sarmah, Sanjib Kr. Kalita . A Survey on Trends and Techniques used in Hyperspectral Image Processing. International Journal of Computer Applications. 122, 9 ( July 2015), 1-8. DOI=10.5120/21725-4879

@article{ 10.5120/21725-4879,
author = { Sonia Sarmah, Sanjib Kr. Kalita },
title = { A Survey on Trends and Techniques used in Hyperspectral Image Processing },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 9 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number9/21725-4879/ },
doi = { 10.5120/21725-4879 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:05.195727+05:30
%A Sonia Sarmah
%A Sanjib Kr. Kalita
%T A Survey on Trends and Techniques used in Hyperspectral Image Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 9
%P 1-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recent advancement in remote sensing facilitates collection of hyperspectral images (HSIs) in hundreds of bands which provides a potential platform to detect and identify the unique trends in land and atmospheric datasets with high accuracy. But along with the detailed information, HSIs also pose several processing problems such as- 1) increase in computational complexity due to high dimensionality. So dimension reduction without losing information is one of the major concerns in this area and 2) limited availability of labeled training sets causes the ill posed problem which is needed to be addressed by the classification algorithms. Initially classification techniques of HSIs were based on spectral information only. Gradually researchers started utilizing both spectral and spatial information to increase classification accuracy. Also the classification algorithms have evolved from supervised to semi supervised mode. This paper presents a survey about the techniques available in the field of HSI processing to provide a seminal view of how the field of HSI analysis has evolved over the last few decades and also provides a snapshot of the state of the art techniques used in this area.

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Index Terms

Computer Science
Information Sciences

Keywords

Hyperspectral images (HSIs) remote sensing dimension reduction ill-posed problem

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