A hybrid approach to fuzzy land cover mapping
| Autor: | Elisabetta Binaghi, Pietro Alessandro Brivio, Paolo Ghezzi, Anna Rampini, Eugenio Zilioli |
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| Rok vydání: | 1996 |
| Předmět: |
Remote sensing image classification
business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Land cover Mixture model Class discrimination Fuzzy logic Domain (software engineering) Identification (information) ComputingMethodologies_PATTERNRECOGNITION Artificial Intelligence Salient Signal Processing Computer Vision and Pattern Recognition Artificial intelligence business Software |
| Zdroj: | ResearcherID |
| ISSN: | 0167-8655 |
| DOI: | 10.1016/s0167-8655(96)00096-7 |
| Popis: | We propose here a fuzzy hybrid methodology for the classification, conceived as a cognitive process, of remote sensing images. The salient aspect of the approach is the combined use of different techniques: the linear mixture model , a supervised fuzzy statistical classifier and a fuzzy labeling technique. An application for the identification of rice crops in a Landsat Thematic Mapper image has been developed with the aim of experimentally evaluating the performance of the overall strategy in a real domain where fuzzy membership to classes are essential in class discrimination. The results have then been compared with those obtained by means of the Maximum Likelihood classifier. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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