Title :
New object-oriented approach for urban objects extraction from VHSR images
Author :
Sebari, Imane ; He, Dong-Chen
Author_Institution :
Univ. de Sherbrooke, Sherbrooke
Abstract :
The goal of our research is to develop a new object-oriented approach of image analysis for extraction of urban objects from very high spatial resolution images. The proposed approach is constituted of two stages: a passage of pixels to primitive objects and a passage of primitives to final objects. The first stage leaves from pixels to create primitives of objects by using a new multispectral non parametric segmentation approach. For the second stage, it is based on a fuzzy rule base and a spatial analysis. The proposed approach was applied on an Ikonos image of Sherbrooke (Canada). A confrontation with the ground truth gave a rate of 85% of good detection. These results are encouraging because the new approach does not requires any prior information or training data.
Keywords :
feature extraction; fuzzy systems; image segmentation; object detection; remote sensing; Ikonos image; Sherbrooke; VHSR images; fuzzy rule base; image analysis; multispectral nonparametric segmentation; object-oriented approach; spatial analysis; urban objects extraction; very high spatial resolution images; Data mining; Helium; Image analysis; Image edge detection; Image segmentation; Information analysis; Pixel; Spatial resolution; Testing; Training data; fuzzy rule base; object-oriented; objects extraction; segmentation;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-1211-2
Electronic_ISBN :
978-1-4244-1212-9
DOI :
10.1109/IGARSS.2007.4423938