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A prior probability method for smoothing discriminant analysis classification maps |
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| Authors: | Paul Switzer William S Kowalik and Ronald J P Lyon |
| Institution: | (1) Department of Statistics, Stanford University, Stanford, California, USA;(2) Department of Applied Earth Sciences, Stanford University, Stanford, California, USA;(3) Present address: Chevron Oil Field Research Co., P.O. Box 446, LaHabra, California, USA |
| Abstract: | A statistical method is presented for smoothing discriminant analysis classification maps by including pixel-specific prior probability estimates that have been determined from the frequency of tentative class assignments in a window moving across an initial per-point classification map. The class at the center of the window is reevaluated using the data for that location and the prior probability estimates obtained from the window area. An example using Landsat spectral data demonstrates the effectiveness of the method and shows an increase in classification accuracy after smoothing. |
| Keywords: | smoothing discriminant analysis remote sensing satellite imagery |
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