In this work, we propose a framework to help in the design of the ground-truth for the classification of remote sensing images. It consists first to segment the considered image by means of a level set method and then to extract the segments characterized by the largest numbers of pixels. Afterward, the selected segments are labeled by a human user. Experimental results obtained on a very high resolution image show encouraging performances of the proposed framework. © 2011 IEEE.
Ground-truth assisted design for remote sensing image classification / Pasolli, E.; Melgani, F.. - (2011), pp. 609-612. (Intervento presentato al convegno 2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 tenutosi a Vancouver, BC, can nel 2011) [10.1109/IGARSS.2011.6049202].
Ground-truth assisted design for remote sensing image classification
Pasolli E.;
2011
Abstract
In this work, we propose a framework to help in the design of the ground-truth for the classification of remote sensing images. It consists first to segment the considered image by means of a level set method and then to extract the segments characterized by the largest numbers of pixels. Afterward, the selected segments are labeled by a human user. Experimental results obtained on a very high resolution image show encouraging performances of the proposed framework. © 2011 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
