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Detection of Targets in Terrain Clutter by Using Multispectral Infrared Image Processing

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Bibliographic Details
Title: Detection of Targets in Terrain Clutter by Using Multispectral Infrared Image Processing
Authors: NAVAL OCEAN SYSTEMS CENTER SAN DIEGO CA, Hoff, L. E., Evans, J. R., Bunney, L. E.
Source: DTIC AND NTIS
Publisher Information: 1990-12
Document Type: Electronic Resource
Abstract: A weighted-difference signal-processing algorithm for detecting ground targets by using dual-band IR data was investigated. Three variations of the algorithm were evaluated: (1) simple difference; (2) minimum noise; and (3) maximum SNR. The theoretical performance was compared to measured performance for two scenes collected by the NASA TIMS sensor over a rural area near Adelaide, Australia, and over a wooded area near the Redstone Arsenal. The theoretical and measured results agreed extremely well. For a given correlation coefficient and color ratio, the amount of signal-to-noise ratio gain can be predicted. However, target input SNRs and color ratios can vary considerably. For the targets and scenes evaluated here, the typical gains achieved ranged from a few dB loss (targets without color) to a maximum.
Index Terms: Infrared Detection and Detectors, IMAGE PROCESSING, INFRARED DETECTORS, RATIOS, DETECTION, CLUTTER, SIGNAL TO NOISE RATIO, TERRAIN, TARGETS, RURAL AREAS, INFRARED IMAGES, COEFFICIENTS, COLORS, GAIN, AUSTRALIA, SURFACE TARGETS, MULTISPECTRAL, INPUT, ALGORITHMS, CORRELATION, MULTISPECTRAL PROCESSING, PE63226E, WUDN388563, Text
URL: https://apps.dtic.mil/docs/citations/ADA237436
Availability: Open access content. Open access content
Approved for public release; distribution is unlimited.
Note: text/html
English
Other Numbers: DTICE ADA237436
832045310
Contributing Source: From OAIster®, provided by the OCLC Cooperative.
Accession Number: edsoai.ocn832045310
Database: OAIster
Description
Abstract:A weighted-difference signal-processing algorithm for detecting ground targets by using dual-band IR data was investigated. Three variations of the algorithm were evaluated: (1) simple difference; (2) minimum noise; and (3) maximum SNR. The theoretical performance was compared to measured performance for two scenes collected by the NASA TIMS sensor over a rural area near Adelaide, Australia, and over a wooded area near the Redstone Arsenal. The theoretical and measured results agreed extremely well. For a given correlation coefficient and color ratio, the amount of signal-to-noise ratio gain can be predicted. However, target input SNRs and color ratios can vary considerably. For the targets and scenes evaluated here, the typical gains achieved ranged from a few dB loss (targets without color) to a maximum.