首页 >  2008, Vol. 12, Issue (4) : 1993-2002

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10.11834/jrs.20080481

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基于链码优化的SAR影像城市道路网络提取
1.中国测绘科学研究院,北京 100039;2.中国矿业大学环境与测绘学院,江苏 徐州 221008
摘要:

针对传统的基于局部比率的道路提取算子存在道路展宽与定位精确性差的缺点,通过加入一个修剪窗口进行改进,有助于去除河流、树木等的影响,且得到了细化和定位更加准确的道路图谱.首次将链码用于道路连接表示,定义了链码能量网络,并将道路的先验知识引入,然后在对模拟道路图像线段连接概率分析的基础上得到了链码优化算法.由于该方法采用了分线运算,每次迭代不需要搜索整个道路片段,提高了运算效率.最后将该算法应用于真实SAR影像巾道路网络的提取,证明了它的有效性.

Road Network Extraction of Urban Areas in SAR Image Based on Optimization of Chain Code
Abstract:

Currently, synthetic aperture radar (SAR) is a hot research topic in the field ofMicrowaveRemote Sensing.Itpossessesmany incomparable advantages such as the capability towork at all tmi e and under allweather, high spatial resolution and strong penetrability through the ground surface and so on. Therefore, it is significant to extract information from SAR mi agery. It can not only compensate the deficiency in optical mi agery, but also help constructing the spatial database.Road information is a kind ofmost mi portant spatial basic information, which has a lot of significant applications,includingmilitary defense,mapmatching, database updating etc. Ratio of average(RoA) algorithm is a classicalmethod for road extraction from SAR mi agery developed in recent 20 years, however, because of SAR speckle noise and other factors, it stillhas some disadvantages. For example: low locality accuracy, thickened edges, higher false alarming rate and non-continuous road segments.Thispaper ismainlydivided into two sections to resolve these problems. In the firstsection,it introduces a local ratio detector for road extraction. But ithasdefectson the accuracy ofposition andwidening roadwidth. In order to tacle these problems,a pruningwindow is added into the process, which is used to remove effects of rivers and trees. Therefore, a thinned andmore accurate road map can be gained. Based on the above method , in the second section , we firstly describe the road linkingmethod using chain codes, define the chain code energy network and mi port the priorknowledge into processing course. Then, we analyze linking probability of line element in smi ulated road map and propose an approach to optmi ize the chain codes. Because the process is programmedwith classed computation, and need no search for all line segments so that it mi proves efficiency highly. At last, thismethod is applied to extracting the road network from realSAR mi age and its validity has been proved.

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