Radar Image Processing for Rock-Type Discrimination

Radar images have unique radiometric and geometric characteristics which present unique problems and opportunities for geological application. This paper reviews preprocessing and analytical techniques found useful or promising for applications of radar images to geologic problems such as rock-type...

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Veröffentlicht in:IEEE transactions on geoscience and remote sensing 1982-07, Vol.GE-20 (3), p.343-351
Hauptverfasser: Blom, Ronald G., Daily, Michael
Format: Artikel
Sprache:eng
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Zusammenfassung:Radar images have unique radiometric and geometric characteristics which present unique problems and opportunities for geological application. This paper reviews preprocessing and analytical techniques found useful or promising for applications of radar images to geologic problems such as rock-type discrimination. The use of coherent monochromatic illumination in radar images results in image speckle noise which interferes with characterization of the imaged surface. Median value filtering of the radar images removes speckle with minimal edge effects and resolution degradation. Variations in radar scene illumination due to uncompensated sensor platform motions or antenna pattern effects can be somewhat corrected for by mean and variance equalization in a direction perpendicular to the resulting image gradient. Registration of radar images to a map base and compensation of terrain induced image distortion can be accomplished by registration to digital elevation models and knowledge of imaging geometry. Analysis of SEASAT images with coregistered LANDSAT images indicates that the radar data can make a significant contribution to rock-type discrimination, especially if textural measures are incorporated. The sensitivity of radar backscatter to local slopes makes radar images an excellent medium from which to extract textural measures. Three techniques for extraction of the textural data inherent in the radar images are presented. Computation of image tone variance over various areas can numerically encode image texture. Hue-saturation-intensity split spectrum processing displays low-frequency variations in color while preserving high-frequency detail.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.1982.350453