Gómez González, DanielMontero De Juan, Francisco Javier2023-06-202023-06-202008Gomez, D., Montero, J.: Fuzzy sets in remote sensing classification. Soft Comput. 12, 243-249 (2007). https://doi.org/10.1007/s00500-007-0201-z1432-764310.1007/s00500-007-0201-zhttps://hdl.handle.net/20.500.14352/50094Supervised classification in remote sensing is a very complex problem and involves steps of different nature, including a serious data preprocessing. The final objective can be stated in terms of a classification of isolated pixels between classes, which can be either previously known or not (for example, different land uses), but with no particular shape nither well defined borders. Hence, a fuzzy approach seems natural in order to capture the structure of the image. In this paper we stress that some useful tools for a fuzzy classification can be derived from fuzzy coloring procedures, to be extended in a second stage to the complete non visible spectrum. In fact, the image is considered here as a fuzzy graph defined on the set of pixels, taking advantage of fuzzy numbers in order to summarize information. A fuzzy model is then presented, to be considered as a decision making aid tool. In this way we generalize the classical definition of fuzzy partition due to Ruspini, allowing in addition a first evaluation of the quality of the classification in this way obtained, in terms of three basic indexes (measuring covering, relevance and overlapping of our family of classes).engjournal articlehttps//doi.org/10.1007/s00500-007-0201-zhttp://www.springerlink.com/content/462841hxl7l71g53/fulltext.pdfrestricted access519.22Fuzzy classification systemsRemote sensingFuzzy graphEstadística matemática (Matemáticas)1209 Estadística