利用边缘密度特征提取高分辨率遥感影像中的居民区

[1] Classification and feature extraction for remote sensing images from urban areas based on morphological transformations. Benediktsson, Jon Atli,Pesaresi, Martino,Arnason, Kolbeinn. IEEE Transactions on Geoscience and Remote Sensing . 2003

[2] Mean shift: a robust approach toward feature space analysis. Comaniciu, D.,Meer, P. Pattern Analysis and Machine Intelligence, IEEE Transactions on . 2002

[3] Real-time tracking of non-rigid objects using mean shift. Dorin Comaniciu,Visvanathan Ramesh,Peter Meer. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition . 2000

[4] Local Edge Distributions for Detection of Salient Structure Textures and Objects. Xiangyun Hu,Jiajie Shen,Jie Shan,Li Pan. Geoscience and Remote Sensing Letters, IEEE . 2013

[5] Application ofProjection Learning to the Detection of Urban Areasin SPOT Satellite Images. Weigl K,Giraudon G,Berthod M. Rapports de recherche-INRIA . 1993

[6] A threshold selection method from gray-level histograms. Otsu N. IEEE Transactions on Systems Man and Cybernetics . 1979

[7] Decision Fusion for the Classification of Urban Remote Sensing Images. Fauvel, M.,Chanussot, J.,Benediktsson, J.A. Geoscience and Remote Sensing, IEEE Transactions on . 2006

[8] Residential area information extraction by combining China airborne SAR and optical images. W. Fan,W. Chao,and Z. Hong. IEEE International Geoscience and Remote Sensing Symposium(IGARSS ‘04) . 2004

[9] Urban area detection using local feature points and spatial voting. Sirmacek, Beril,Unsalan, Cem. IEEE Geoscience and Remote Sensing Letters . 2010

[10] A multiple conditional random fields ensemble model for urban area detection in remote sensing optical images. Zhong, Ping,Wang, Runsheng. IEEE Transactions on Geoscience and Remote Sensing . 2007

[1] Classification and feature extraction for remote sensing images from urban areas based on morphological transformations. Benediktsson, Jon Atli,Pesaresi, Martino,Arnason, Kolbeinn. IEEE Transactions on Geoscience and Remote Sensing . 2003

[2] Mean shift: a robust approach toward feature space analysis. Comaniciu, D.,Meer, P. Pattern Analysis and Machine Intelligence, IEEE Transactions on . 2002

[3] Real-time tracking of non-rigid objects using mean shift. Dorin Comaniciu,Visvanathan Ramesh,Peter Meer. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition . 2000

[4] Local Edge Distributions for Detection of Salient Structure Textures and Objects. Xiangyun Hu,Jiajie Shen,Jie Shan,Li Pan. Geoscience and Remote Sensing Letters, IEEE . 2013

[5] Application ofProjection Learning to the Detection of Urban Areasin SPOT Satellite Images. Weigl K,Giraudon G,Berthod M. Rapports de recherche-INRIA . 1993

[6] A threshold selection method from gray-level histograms. Otsu N. IEEE Transactions on Systems Man and Cybernetics . 1979

[7] Decision Fusion for the Classification of Urban Remote Sensing Images. Fauvel, M.,Chanussot, J.,Benediktsson, J.A. Geoscience and Remote Sensing, IEEE Transactions on . 2006

[8] Residential area information extraction by combining China airborne SAR and optical images. W. Fan,W. Chao,and Z. Hong. IEEE International Geoscience and Remote Sensing Symposium(IGARSS ‘04) . 2004

[9] Urban area detection using local feature points and spatial voting. Sirmacek, Beril,Unsalan, Cem. IEEE Geoscience and Remote Sensing Letters . 2010

[10] A multiple conditional random fields ensemble model for urban area detection in remote sensing optical images. Zhong, Ping,Wang, Runsheng. IEEE Transactions on Geoscience and Remote Sensing . 2007