Hyperspectral Target Detection Using Segmented Matched Filter with Local Covariance Reassignment

Haim Elisha, Stanley Rotman

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

Abstract

Segmentation is useful during sub-pixel target detection in hyperspectral data. Our standard algorithm uses estimates of the actual pixel being examined (based on surrounding pixels) and of the covariance matrix of the background (traditionally based on all the pixels in the image). Previous works have showed that improving performance in sub-pixel target detection can be achieved by making better estimates of the covariance matrix by using segmentation. One of the challenges is that pixel assignment to its segment can be influenced by the presence of the target that will lead us to miss the target. Therefore, it is desirable to assign the examined pixel by using the neighbors of the pixel assignment without involving the pixel itself is needed. We developed a new reassignment segmentation without involving the central pixel. Using simulations and several analytical tools, we analyzed the matched-filter algorithm, both with and without segmentation, and compare performances of the receiver operating characteristic curves. Our algorithm showed better receiver operating characteristic curves in low false positive rate in the range 0-0.01 (the operating range of our applications), i.e., we got a higher true positive rate for the same false positive rate.

Original languageEnglish
Title of host publication2022 12th Workshop on Hyperspectral Imaging and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing, WHISPERS 2022
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781665470698
DOIs
StatePublished - 1 Jan 2022
Event12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2022 - Rome, Italy
Duration: 13 Sep 202216 Sep 2022

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volume2022-September
ISSN (Print)2158-6276

Conference

Conference12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2022
Country/TerritoryItaly
CityRome
Period13/09/2216/09/22

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

  • Computer Vision and Pattern Recognition
  • Signal Processing

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