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Comparing Pixels on target with NV-IPM range predictions

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There is growing interest in applying machine learning algorithms to target acquisition tasks. Current algorithm studies suggest pixels on target area (POT) of 50-70, 150, 250, and 350 are adequate for detection, classification, recognition, and identification of tank-sized targets respectively. Using simple analyzes, we compare POT to Night Vision Integrated Performance Model (NV-IPM) range probability predictions for a typical LWIR sensor.

Original languageEnglish (US)
Title of host publicationInfrared Imaging Systems
Subtitle of host publicationDesign, Analysis, Modeling, and Testing XXXIV
EditorsGerald C. Holst, David P. Haefner
PublisherSPIE
ISBN (Electronic)9781510661806
DOIs
StatePublished - 2023
EventInfrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV 2023 - Orlando, United States
Duration: May 3 2023May 4 2023

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12533
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceInfrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV 2023
Country/TerritoryUnited States
CityOrlando
Period5/3/235/4/23

Keywords

  • Edge response
  • equivalent resolution
  • NIIRS
  • NV-IPM
  • pixels on target
  • POT

ASJC Scopus subject areas

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

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