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Minimum distance classification in remote sensing
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Wacker, A. G. Landgrebe, D. A. |
| Copyright Year | 1972 |
| Description | The utilization of minimum distance classification methods in remote sensing problems, such as crop species identification, is considered. Literature concerning both minimum distance classification problems and distance measures is reviewed. Experimental results are presented for several examples. The objective of these examples is to: (a) compare the sample classification accuracy of a minimum distance classifier, with the vector classification accuracy of a maximum likelihood classifier, and (b) compare the accuracy of a parametric minimum distance classifier with that of a nonparametric one. Results show the minimum distance classifier performance is 5% to 10% better than that of the maximum likelihood classifier. The nonparametric classifier is only slightly better than the parametric version. |
| File Size | 1874553 |
| Page Count | 26 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19730007762 |
| Archival Resource Key | ark:/13960/t1wd8mv7b |
| Language | English |
| Publisher Date | 1972-02-09 |
| Access Restriction | Open |
| Subject Keyword | Remote Sensors Classifiers Earth Resources Performance Data Sampling Distance Measuring Equipment Crop Identification Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Article |
