Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/46182
Título: Classification of PolSAR imagery by solving a diffusion-reaction system
Autores/as: Gomez, Luis 
Alvarez, Luis 
Mazorra, Luis 
Frery, Alejandro C. 
Clasificación UNESCO: 220990 Tratamiento digital. Imágenes
120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
120326 Simulación
Palabras clave: Stochastic Distances
Wishart
Fecha de publicación: 2015
Editor/a: Institute of Electrical and Electronics Engineers (IEEE) 
Conferencia: 2015 4th International Work Conference on Bioinspired Intelligence (IWOBI) 
4th International Work Conference on Bio-Inspired Intelligence, IWOBI 2015 
Resumen: PolSAR (Polarimetric Syntethic Aperture Radar) imagery classification plays an essential role in monitoring remote sensing data. Such classification is a difficult task due to the speckle noise which appears in these kind of data. Therefore, there is a need to design new efficient methods to classify PolSAR images. In this work, a new approach to classify PolSAR data is proposed. The method relies on simultaneously filtering and classifying pixels within the image through embedding the problem into a diffusion-reaction partial differential equation system. The diffusion term smooths the patches within the image, and the reaction term tends to move the pixel PolSAR values towards the closest (in some sense) representative class. In particular, the method inherits the benefits of speckle filtering reduction by diffusion-like methods. An iterative schema is stated and, by properly selecting the algorithm control parameters, the user may force the classification to evolve according to her/his requirements to account for other image post-processing tasks (i.e. quantitative analysis to monitor deforestation, drought or urban areas growing). Results on real PolSAR data show the performance of the method, which is evaluated both visually and by means of the confusion matrix, showing an average classification rate 87.56 %
URI: http://hdl.handle.net/10553/46182
ISBN: 9781467378475
9781479961740
DOI: 10.1109/IWOBI.2015.7160147
Fuente: IWOBI 2015 - 2015 International Work Conference on Bio-Inspired Intelligence: Intelligent Systems for Biodiversity Conservation, 10-12 June 2015, San Sebastian, Spain.Proceedings (7160147), p. 73-80
Colección:Actas de congresos
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