Comparison between constrained energy minimization based approaches for hyperspectral imagery

Hsuan Ren, Qian Du, Chein I. Chang, J. O. Jensen

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

37 Scopus citations

Abstract

Constrained Energy Minimization (CEM) has been widely used for target detection in hyperspectral remote sensing imagery. It detects the desired target signal source using a unity constraint while suppressing noise and unknown signal sources by minimizing the average output power. Base on the design CEM can only detect one target source at a time. In order to simultaneously detect multiple targets in a single image, several approaches are developed, including Multiple-Target CEM (MTCEM), Sum CEM (SCEM) and Winner-Take-All CEM (WTACEM). Interestingly, the sensitivity of noise and interference seems to play a role in the detection performance. Unfortunately, this issue has not been investigated. In this paper, we take up this problem and conduct a quantitative study of the noise and interference suppression abilities of LCMV, SCEM, WTACEM for multiple-target detection.

Original languageEnglish
Title of host publication2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages244-248
Number of pages5
ISBN (Electronic)0780383508, 9780780383500
DOIs
StatePublished - 2004
Event2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data - Greenbelt, United States
Duration: 27 Oct 200328 Oct 2003

Publication series

Name2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data

Conference

Conference2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data
Country/TerritoryUnited States
CityGreenbelt
Period27/10/0328/10/03

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