Extraction of road network from high resolution satellite images using ANN

Road extraction in urban areas from high resolution satellite images helps in creating a database of a city and in cartography. The extraction results are intended to be used for updating a road database. The high dimensionality of aerial and satellite imagery presents a challenge to the human analysis based on the traditional classification algorithms using statistical assumptions. Artificial Neural Networks (ANNs) on the other hand may represent a valuable alternative approach for land cover mapping for such highly dimensional imagery. The urban areas contain roads of different shapes, sizes and lengths. In this paper, the extraction algorithm performs edge detection, morphological reconstruction, feature extraction and classification. The road features are classified using ANNs.

[1]  Dan Klang,et al.  AUTOMATIC DETECTION OF CHANGES IN ROAD DATABASES USING SATELLITE IMAGERY , 2003 .

[2]  E. Baltsavias,et al.  Automatic Extraction of Man-Made Objects from Aerial and Space Images (II) , 1995 .

[3]  Stefan Hinz,et al.  AUTOMATIC ROAD EXTRACTION IN URBAN SCENES — AND BEYOND , 2004 .

[4]  David B. L. Bong,et al.  Automatic Road Network Recognition and Extraction for Urban Planning , 2009 .

[5]  David B. Cooper,et al.  Automatic Finding of Main Roads in Aerial Images by Using Geometric-Stochastic Models and Estimation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Xiaoying Jin,et al.  Multispectral IKONOS imagery automatic road extraction from high-resolution , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[7]  A. Grote,et al.  ROAD EXTRACTION IN SUBURBAN AREAS BASED ON NORMALIZED CUTS , 2007 .

[8]  C. Heipke,et al.  ROAD EXTRACTION FOR THE UPDATE OF ROAD DATABASES IN SUBURBAN AREAS , 2008 .

[9]  Kyu Sik Kim,et al.  A road extraction method from topographical map images , 1997, 1997 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, PACRIM. 10 Years Networking the Pacific Rim, 1987-1997.

[10]  Xuan Li,et al.  The research of road extraction for high resolution satellite image , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[11]  Mourad Zribi,et al.  An Optimal Unsupervised Satellite image Segmentation Approach Based on Pearson System and k-Means Clustering Algorithm Initialization , 2009 .

[12]  Wadii Boulila,et al.  Improving Spatiotemporal Change Detection: A High Level Fusion Approach for Discovering Uncertain Knowledge from Satellite Image Database , 2009 .

[13]  Chunsun Zhang.  Towards an operational system for automated updating of road databases by integration of imagery and geodata , 2004 .

[14]  Junhee Youn.  ADAPTIVE SNAKES FOR URBAN ROAD EXTRACTION , 2004 .

[15]  Christian Wiedemann,et al.  AUTOMATIC COMPLETION AND EVALUATION OF ROAD NETWORKS , 2000 .

[16]  Keith Price,et al.  Road Grid Extraction and Verification , 1998 .

[17]  Qiming Qin,et al.  Road Extraction from Remote Sensing Image Based on Multi-resolution Analysis , 2005 .

[18]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[19]  Stefan Hinz,et al.  Automatic extraction of urban road networks from multi-view aerial imagery , 2003 .