DocumentCode :
826889
Title :
On the use of prior and posterior information in the subpixel proportion problem
Author :
Kolaczyk, Eric D.
Author_Institution :
Dept. of Math. & Stat., Boston Univ., MA, USA
Volume :
41
Issue :
11
fYear :
2003
Firstpage :
2687
Lastpage :
2691
Abstract :
Although the problems of classification and subpixel proportion estimation in remote sensing land cover characterization generally are held to be distinct (though related), often elements of the former are adopted in addressing the latter that blur this distinction - particularly, regarding the use of prior and posterior information. The author examines this issue in more detail, using simple, canonical versions of the two problems and, in the course of this examination, provides analytical expressions upon which to build discussion of improvements to subpixel proportion estimation from a statistical viewpoint.
Keywords :
Bayes methods; image classification; vegetation mapping; Bayesian estimation; land cover classification; posterior information; prior information; remote sensing; statistical approach; subpixel proportion estimation; subpixel proportion problem; Ecosystems; Image processing; Interpolation; Mathematics; Monitoring; Pixel; Predictive models; Remote sensing; Satellites; Statistics;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2003.817194
Filename :
1245258
Link To Document :
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