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Recently the major methods of extracting road from remote sensing image are manually. It becomes a hotpot to realize automatic information extraction of road according to the feature of high-resolution image and the characteristics of road. In this paper, an improved approach for road extraction based on Watershed segmentation is proposed according to theories of object-oriented and mathematical morphology. The image is first processed by improved Watershed segmentation to acquire feature-units after preprocessing. Then object-oriented method is used to analyze road feature-units in order to optimize the road extraction results. Finally, after binary image processing, the incomplete results can be removed and corrected by using mathematical morphological transformation. At last this paper gives the result and analysis of the experiment sample.

The research of road extraction from high-resolution remote sensing image based on optimized watershed algorithm