In this paper we address the feature selection problem for X-SAR images and further the segmentation of specific chosen classes. After defining a suitable feature space for X-SAR images we select the most significant ones via a supervised machine learning approach: the 1-norm SVM. The selected features will be used for segmentation purposes, in order to segment water areas from the background. We shall see that the most relevant features are based on texture elements. So the segmentation is texture based and achieved with variational calculus and level set methods. The work is mainly focused on urban park X-SAR SpotLight images, where lakes and rivers are often present. The images are collected with the COSMO-SkyMed satellites constellation, equipped with a SAR sensor. © 2012 IEEE.
X-SAR SpotLigh images feature selection and water segmentation / Cafaro, Bruno; Canale, Silvia; PIRRI ARDIZZONE, Maria Fiora. - ELETTRONICO. - (2012), pp. 217-222. (Intervento presentato al convegno 2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012 tenutosi a Manchester nel 16 July 2012 through 17 July 2012) [10.1109/ist.2012.6295589].
X-SAR SpotLigh images feature selection and water segmentation
CAFARO, BRUNO;CANALE, Silvia;PIRRI ARDIZZONE, Maria Fiora
2012
Abstract
In this paper we address the feature selection problem for X-SAR images and further the segmentation of specific chosen classes. After defining a suitable feature space for X-SAR images we select the most significant ones via a supervised machine learning approach: the 1-norm SVM. The selected features will be used for segmentation purposes, in order to segment water areas from the background. We shall see that the most relevant features are based on texture elements. So the segmentation is texture based and achieved with variational calculus and level set methods. The work is mainly focused on urban park X-SAR SpotLight images, where lakes and rivers are often present. The images are collected with the COSMO-SkyMed satellites constellation, equipped with a SAR sensor. © 2012 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
