DocumentCode
1878045
Title
Ground-truth assisted design for remote sensing image classification
Author
Pasolli, Edoardo ; Melgani, Farid
Author_Institution
Dept. of Inf. Eng. & Comput. Sci., Univ. of Trento, Trento, Italy
fYear
2011
fDate
24-29 July 2011
Firstpage
609
Lastpage
612
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.
Keywords
feature extraction; geophysical image processing; image classification; image resolution; image segmentation; remote sensing; ground-truth assisted design; image classification; level set method; remote sensing; segment extraction; very high resolution image; Humans; Image segmentation; Labeling; Level set; Remote sensing; Support vector machines; Training; Ground-truth design; level set segmentation; support vector machines (SVM); very high resolution (VHR) images;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location
Vancouver, BC
ISSN
2153-6996
Print_ISBN
978-1-4577-1003-2
Type
conf
DOI
10.1109/IGARSS.2011.6049202
Filename
6049202
Link To Document