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Proceedings Paper

Geometric parameter estimation for agriculture fields
Author(s): Liu Lu; Fang Luo; Nanno J. Mulder
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Paper Abstract

Geometric parameter estimation is a common task in remote sensing image processing. Quite often, it is needed to find out the area and location of a certain kind of crop in a remotely sensed image. If we take a parcel of a uniform crop type in a remote sensing image as an object, the task is to determine the orientation, location, and scale of the object. In this paper, we propose a model based method for parameter estimation in which the radiometric distribution obtained by radar simulation is used as a global feature of an object to characterize its spectral properties. A cost function is defined as a quantitative evaluation for the hypothesis of object parameters in terms of its feature fitting and the minimum cost corresponds to the best parameters of the object with the least misclassified pixels. The feature matching is completed through cost minimization. Experiments show that this method is quite efficient especially in the cases of bad signal to noise ratios.

Paper Details

Date Published: 30 December 1994
PDF: 10 pages
Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); doi: 10.1117/12.196755
Show Author Affiliations
Liu Lu, International Institute for Aerospace Survey and Earth Sciences (Netherlands)
Fang Luo, International Institute for Aerospace Survey and Earth Sciences (Netherlands)
Nanno J. Mulder, International Institute for Aerospace Survey and Earth Sciences (Netherlands)


Published in SPIE Proceedings Vol. 2315:
Image and Signal Processing for Remote Sensing
Jacky Desachy, Editor(s)

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