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A statistical model for radar images of agricultural scenesThe presently derived and validated statistical model for radar images containing many different homogeneous fields predicts the probability density functions of radar images of entire agricultural scenes, thereby allowing histograms of large scenes composed of a variety of crops to be described. Seasat-A SAR images of agricultural scenes are accurately predicted by the model on the basis of three assumptions: each field has the same SNR, all target classes cover approximately the same area, and the true reflectivity characterizing each individual target class is a uniformly distributed random variable. The model is expected to be useful in the design of data processing algorithms and for scene analysis using radar images.
Document ID
19830064973
Document Type
Conference Paper
Authors
Frost, V. S. (Kansas Univ. Center for Research, Inc. Lawrence, KS, United States)
Shanmugan, K. S. (Kansas Univ. Center for Research, Inc. Lawrence, KS, United States)
Holtzman, J. C. (Kansas Univ. Center for Research, Inc. Lawrence, KS, United States)
Stiles, J. A. (University of Kansas Center for Research, Inc., Lawrence KS, United States)
Date Acquired
August 11, 2013
Publication Date
January 1, 1982
Subject Category
EARTH RESOURCES AND REMOTE SENSING
Meeting Information
1982 International Geoscience and Remote Sensing Symposium(Munich)
Funding Number(s)
CONTRACT_GRANT: NAG9-3
Distribution Limits
Public
Copyright
Other