An Infrared Model of R/V POINT SUR Using EOPACE Data

Abstract

Infrared polarization techniques to improve the target-background contrast are the subject of much study lately. Polarized infrared images of the research vessel, R/V POINT SUR were taken extensively during the Electro-Optical Propagation Assessment in Coastal Environment (EOPACE) operational period in Mar-Apr 1996 at Point Loma, San Diego. Contrast improvement analysis of these images requires an infrared model of the research vessel. This thesis models the apparent infrared signature of the R/V POINT SUR using ship skin temperature records from the EOPACE measurements. Using a simple geometric model and adopting a pixel-by-pixel approach, the emitted radiation for each pixel surface is calculated from the Planck radiation law. Radiation reflected off the pixel surface is estimated using the polarized SeaRad atmospheric propagation code. The total radiance is compensated for atmospheric transmittance with the Navy Aerosol Model to arrive at the apparent radiance at the sensor. The apparent radiance is translated into apparent temperature for comparison with the recorded images to validate the accuracy of the model. There is moderate agreement between the model and recorded images with 45-50% of the pixels falling within 1.75K of the measured apparent temperatures.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1999
Accession Number
ADA361651

Entities

People

  • Tan C. Yong

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms
  • Biomedical
  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Detectors
  • Environment
  • Geometry
  • Images
  • Infrared Images
  • Infrared Radiation
  • Infrared Signatures
  • Measurement
  • Optical Properties
  • Polarization
  • Radiation
  • Scattering
  • Sea Surface Temperature
  • Surface Temperature
  • Thermal Images
  • Two Dimensional

Fields of Study

  • Physics

Readers

  • Atmospheric Remote Sensing.
  • Image Processing and Computer Vision.
  • Oceanography.