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Urban Roads Extraction Algorithm for High Resolution Remote Sensing Image

Author: ZhaoXiaoFeng
Tutor: TanYiHua
School: Huazhong University of Science and Technology
Course: Pattern Recognition and Intelligent Systems
Keywords: Road Extraction Total Variation Regional Growth Curve fitting Vectorization
CLC: TP751
Type: Master's thesis
Year: 2010
Downloads: 187
Quote: 1
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Abstract


The road is an important artificial surface features , as the skeleton of the city , which has important significance for urban planning, traffic management , etc. to automatically extract and update . In the past decades , although many researchers for road extraction from remote sensing images from different angles proposed some solutions , but the large number of studies have focused extraction of roads in the low-resolution images . The different resolutions roads different forms and features , and with the improvement of remote sensing image resolution , road details and complicated , so very different road extraction method with low resolution high resolution . Therefore, the study has important theoretical and practical significance extracted from the high-resolution images of urban roads . Papers from the spectral characteristics and geometric characteristics of the road , on the urban road network extraction technology of high - resolution remote sensing images , specific content mainly includes the following aspects : First, different resolutions , different context road to analyze the characteristics summarized , combined with previous studies based on the characteristics of the high-resolution images of urban roads , to establish a theoretical foundation for the thesis algorithm . Second , in a detailed analysis based on the total road area variational segmentation algorithm based on a segmentation algorithm based on total variation and the high-resolution remote region growing urban roads , this segmentation method application split in the road area achieved good results . The typical characteristics of the target area in the initial segmentation of remote sensing image analysis, and the use of multiple geometric shape factor to describe the characteristics of the shape of the image segmentation of the two types of typical road area , to complete the work of non- road area of the filter . Finally, on the basis of region segmentation using morphological skeleton extraction and curve fitting techniques to extract the skeleton of the urban road network , and trim optimization , and vector processing in order to extract a more complete urban road network . information . Papers selected several different areas in the high-resolution image data experimental results show that the method can extract urban road network information .

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CLC: > Industrial Technology > Automation technology,computer technology > Remote sensing technology > Interpretation, identification and processing of remote sensing images > Image processing methods
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