Use of probability entropy for the estimation and graphical representation of the accuracy of maximum likelihood classifications
| Autor: | Fabio Maselli, Claudio Conese, Ljiljana Petkov |
|---|---|
| Rok vydání: | 1994 |
| Předmět: |
business.industry
Restricted maximum likelihood Estimation theory Pattern recognition Maximum likelihood sequence estimation Likelihood principle Atomic and Molecular Physics and Optics Computer Science Applications Likelihood-ratio test Statistics Expectation–maximization algorithm Entropy (information theory) Artificial intelligence Computers in Earth Sciences Likelihood function business Engineering (miscellaneous) Mathematics |
| Zdroj: | ISPRS journal of photogrammetry and remote sensing 49 (1994): 13–20. info:cnr-pdr/source/autori:F. MASELLI, C. CONESE, L. PETKOV/titolo:Use of Probability Entropy for the Estimation and Graphical Representation of the Accuracy of Maxi¬mum Likelihood Classifications/doi:/rivista:ISPRS journal of photogrammetry and remote sensing/anno:1994/pagina_da:13/pagina_a:20/intervallo_pagine:13–20/volume:49 |
| ISSN: | 0924-2716 |
| DOI: | 10.1016/0924-2716(94)90062-0 |
| Popis: | A method is proposed for statistically evaluating the accuracy levels of maximum likelihood classifications and representing them graphically. Based on the concept that the heterogeneity of maximum likelihood membership probabilities can be taken as an indicator of the confidence for the classification, such a parameter is estimated for all pixels as relative probability entropy and represented in a separate channel. After a brief presentation of the statistical basis of the methodology, this is applied to a conventional and two modified maximum likelihood classifications in a case study using Landsat TM scenes. The results demonstrate the efficiency of the approach and, particularly, its usefulness for operational applications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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