Analysis of standard deviation normalization in segmented target detection algorithm

Haim Elisha, Stanley Rotman

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

Abstract

This article presents a novel method for point target detection in remote sensing imagery, focusing on the development of an innovative approach to enhance detection accuracy and reduce false positives. The core contribution of this research lies in the refinement of traditional point target detection algorithms by introducing a targeted strategy to exclude edge artifacts and seamlessly integrating the methodology into a segmented matched filter framework. In this research we will expand the matched filter standard deviation filter (1) to the segmented matched filter.

Original languageEnglish
Title of host publicationElectro-Optical and Infrared Systems
Subtitle of host publicationTechnology and Applications XXI
EditorsDuncan L. Hickman, Helge Bursing, Ove Steinvall, Philip J. Soan
PublisherSPIE
ISBN (Electronic)9781510681088
DOIs
StatePublished - 1 Jan 2024
EventElectro-Optical and Infrared Systems: Technology and Applications XXI 2024 - Edinburgh, United Kingdom
Duration: 16 Sep 202419 Sep 2024

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume13200
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceElectro-Optical and Infrared Systems: Technology and Applications XXI 2024
Country/TerritoryUnited Kingdom
CityEdinburgh
Period16/09/2419/09/24

Keywords

  • Covariance matrix
  • False positive rate (FPR)
  • Hyperspectral
  • Matched filter
  • Receiver operation characteristic (ROC) curve
  • Segmentation
  • Subpixel target detection
  • True positive rate (TPR)

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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