Detection of Targets in Terrain Clutter by Using Multispectral Infrared Image Processing
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| Název: | Detection of Targets in Terrain Clutter by Using Multispectral Infrared Image Processing |
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| Autoři: | NAVAL OCEAN SYSTEMS CENTER SAN DIEGO CA, Hoff, L. E., Evans, J. R., Bunney, L. E. |
| Zdroj: | DTIC AND NTIS |
| Informace o vydavateli: | 1990-12 |
| Druh dokumentu: | Electronic Resource |
| Abstrakt: | 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. |
| Témata: | 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: | |
| Dostupnost: | Open access content. Open access content Approved for public release; distribution is unlimited. |
| Poznámka: | text/html English |
| Other Numbers: | DTICE ADA237436 832045310 |
| Přispívající zdroj: | From OAIster®, provided by the OCLC Cooperative. |
| Přístupové číslo: | edsoai.ocn832045310 |
| Databáze: | OAIster |
| Abstrakt: | 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. |
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