Extraction Technology Research, Remote Sensing Image Of The Model Constraint-based Road Smart

With the rapid development of RS, man can get more and more aerial and satellite imagery. Thus, automated information acquisition from imagery has become a bottleneck, which needs to be overcome. Road networks are important geographical thematic information of satellite imagery. In the past, automatic road extraction from digital imagery has received considerable attention. Automatic road extraction from satellite imagery is studied in this paper and the main works are summarized as below:1. Introducing the background of research and the development trend of road extraction.2. An automatic road extraction strategy is introduced based on Cognitive Psychology and Perceptual Organization Theory, emphasizing the leading action of high-layer knowledge.3. The road feature of low-resolution imagery is analyzed in detail and the road description model is built on Vosselman and Knecht's definition about the road knowledge.4. Describing an automatic road extraction approach based on Perceptual Organization. Road segments are regrouped under global knowledge lead after being grouped on purely local criteria, which reduces the disadvantage of local grouping.5. A Heuristic Graph Search algorithm used to extract road semi-automatically mainly from low-resolution satellite imagery is presented.