Method Based on Edge Constraint and Fast Marching for Road Centerline Extraction from Very High-Resolution Remote Sensing Images

In recent decades, road extraction from very high-resolution (VHR) remote sensing images has become popular and has attracted extensive research efforts. However, the very high spatial resolution, complex urban structure, and contextual background effect of road images complicate the process of road extraction. For example, shadows, vehicles, or other objects may occlude a road located in a developed urban area. To address the problem of occlusion, this study proposes a semiautomatic approach for road extraction from VHR remote sensing images. First, guided image filtering is employed to reduce the negative effects of nonroad pixels while preserving edge smoothness. Then, an edge-constraint-based weighted fusion model is adopted to trace and refine the road centerline. An edge-constraint fast marching method, which sequentially links discrete seed points, is presented to maintain road-point connectivity. Six experiments with eight VHR remote sensing images (spatial resolution of 0.3 m/pixel to 2 m/pixel) are conducted to evaluate the efficiency and robustness of the proposed approach. Compared with state-of-the-art methods, the proposed approach presents superior extraction quality, time consumption, and seed-point requirements.

[1]  Haihong Li,et al.  Road extraction from aerial and satellite images by dynamic programming , 1995 .

[2]  Wenzhong Shi,et al.  Correction to "Extracting Man-Made Objects From High Spatial Resolution Remote Sensing Images via Fast Level Set Evolutions" , 2015, IEEE Trans. Geosci. Remote. Sens..

[3]  Jean Daunizeau,et al.  Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography , 2007, Int. J. Biomed. Imaging.

[4]  Stephen T. C. Wong,et al.  Diffusion tensor-based fast marching for modeling human brain connectivity network , 2011, Comput. Medical Imaging Graph..

[5]  Yao Yu,et al.  Joint Enhancing Filtering for Road Network Extraction , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Christian Heipke,et al.  EMPIRICAL EVALUATION OF AUTOMATICALLY EXTRACTED ROAD AXES , 1998 .

[7]  Wenzhong Shi,et al.  Road Centerline Extraction From High-Resolution Imagery Based on Shape Features and Multivariate Adaptive Regression Splines , 2013, IEEE Geoscience and Remote Sensing Letters.

[8]  Sébastien Lefèvre,et al.  Morphological path filtering at the region scale for efficient and robust road network extraction from satellite imagery , 2016, Pattern Recognit. Lett..

[9]  Pascal Fua,et al.  Automated reconstruction of tree structures using path classifiers and Mixed Integer Programming , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[10]  Jun Zhou,et al.  ROBUST AND EFFICIENT ROAD TRACKING IN AERIAL IMAGES , 2005 .

[11]  Wenzhong Shi,et al.  Extracting Man-Made Objects From High Spatial Resolution Remote Sensing Images via Fast Level Set Evolutions , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[12]  A. ROSENFELD,et al.  Distance functions on digital pictures , 1968, Pattern Recognit..

[13]  Juan B. Mena,et al.  State of the art on automatic road extraction for GIS update: a novel classification , 2003, Pattern Recognit. Lett..

[14]  Ying Wang,et al.  Accurate urban road centerline extraction from VHR imagery via multiscale segmentation and tensor voting , 2015, Neurocomputing.

[15]  Jan Dirk Wegner,et al.  A Higher-Order CRF Model for Road Network Extraction , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[16]  Liujuan Cao,et al.  Road Network Extraction via Aperiodic Directional Structure Measurement , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Manchun Li,et al.  Multi-points fast marching: A novel method for road extraction , 2010, 2010 18th International Conference on Geoinformatics.

[18]  Liangpei Zhang,et al.  Classification and Extraction of Spatial Features in Urban Areas Using High-Resolution Multispectral Imagery , 2007, IEEE Geoscience and Remote Sensing Letters.

[19]  Alfred Stein,et al.  Region-based urban road extraction from VHR satellite images using Binary Partition Tree , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[20]  Xin Huang,et al.  Road centreline extraction from high‐resolution imagery based on multiscale structural features and support vector machines , 2009 .

[21]  Yonghong Jia,et al.  An Adaptive Multifeature Sparsity-Based Model for Semiautomatic Road Extraction From High-Resolution Satellite Images in Urban Areas , 2017, IEEE Geoscience and Remote Sensing Letters.

[22]  Wenzhong Shi,et al.  An Integrated Method for Urban Main-Road Centerline Extraction From Optical Remotely Sensed Imagery , 2014, IEEE Transactions on Geoscience and Remote Sensing.

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

[24]  Mehdi Maboudi,et al.  Road Network Extraction from VHR Satellite Images Using Context Aware Object Feature Integration and Tensor Voting , 2016, Remote. Sens..

[25]  Mehdi Mokhtarzade,et al.  Road detection from high-resolution satellite images using artificial neural networks , 2007, Int. J. Appl. Earth Obs. Geoinformation.

[26]  Peerapon Vateekul,et al.  Road Segmentation of Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields , 2017, Remote. Sens..

[27]  Wim Bakker,et al.  Hyperspectral edge filtering for measuring homogeneity of surface cover types , 2002 .

[28]  Nan Yang,et al.  A review of road extraction from remote sensing images , 2016 .

[29]  X. G. Lina,et al.  SEMI-AUTOMATIC EXTRACTION OF RIBBON ROADS FORM HIGH RESOLUTION REMOTELY SENSED IMAGERY BY COOPERATION BETWEEN ANGULAR TEXTURE SIGNATURE AND TEMPLATE MATCHING , 2008 .

[30]  Jian Sun,et al.  Guided Image Filtering , 2010, ECCV.

[31]  Feiping Nie,et al.  Learning a Mahalanobis distance metric for data clustering and classification , 2008, Pattern Recognit..

[32]  Ibrahim Ahamada,et al.  Non-Parametric Econometrics , 2011 .

[33]  Christian Heipke,et al.  Network snakes: graph-based object delineation with active contour models , 2010, Machine Vision and Applications.

[34]  Wenzhong Shi,et al.  A Semi-Automatic Method for Road Centerline Extraction From VHR Images , 2014, IEEE Geoscience and Remote Sensing Letters.

[35]  T. T. Mirnalinee,et al.  An Integrated Multistage Framework for Automatic Road Extraction from High Resolution Satellite Imagery , 2011 .

[36]  Ying Wang,et al.  Urban road extraction via graph cuts based probability propagation , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[37]  Paolo Gamba,et al.  An Object-Based Method for Road Network Extraction in VHR Satellite Images , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[38]  J. Sethian,et al.  Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .

[39]  Sukhendu Das,et al.  Use of Salient Features for the Design of a Multistage Framework to Extract Roads From High-Resolution Multispectral Satellite Images , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[40]  Zuxun Zhang,et al.  A Robust Method for Semi-Automatic Extraction of Road Centerlines Using a Piecewise Parabolic Model and Least Square Template Matching , 2004 .

[41]  Peter Wonka,et al.  Road Network Extraction and Intersection Detection From Aerial Images by Tracking Road Footprints , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[42]  Sahar Movaghati,et al.  Road Extraction From Satellite Images Using Particle Filtering and Extended Kalman Filtering , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[43]  Aluir Porfírio Dal Poz,et al.  Object-Space Road Extraction in Rural Areas Using Stereoscopic Aerial Images , 2012, IEEE Geoscience and Remote Sensing Letters.

[44]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[45]  Shi Wen.  Road Feature Extraction from Remotely Sensed Image:Review and Prospects , 2001 .

[46]  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..

[47]  Paolo Gamba,et al.  Information Fusion for Urban Road Extraction From VHR Optical Satellite Images , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.