Examining Change Detection Methods for Hyperspectral Data

Barak Radomsky, Adi Daniel, Stanley R. Rotman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The requirement for change detection in hyperspectral data appears to be an important and necessary tool in a variety of fields such as military, medical, geology, etc. The main objective of change detection is to observe changes of the probability distribution of a stochastic process. In this paper, we analyze two detection methods which were introduced by Schaum Stocker: chronochrome and covariance equalization. We observe the viability of both methods for when there is misregistration between the images and determine which one is better than the other at finding anomalies.

Original languageEnglish
Title of host publication2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538663783
DOIs
StatePublished - 20 Feb 2019
Event2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 - Eilat, Israel
Duration: 12 Dec 201814 Dec 2018

Publication series

Name2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018

Conference

Conference2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
Country/TerritoryIsrael
CityEilat
Period12/12/1814/12/18

Keywords

  • Chronochrome
  • Covariance equalization
  • Hyperspectral imaging
  • Target detection

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