A Method for Automatic Object Extraction in High-resolution Remote Sensing Image
一种高分辨率遥感图像目标自动提取方法

In this paper, a method for automatic object extraction in high-resolution remote sensing image is proposed. First, a robust multilayer classifier is employed to detect the object efficiently. Secondly, a cost function based on the color model and the smoothness prior knowledge is built up and minimized to segment the object accurately. Lastly, in the post processing stage, the shape prior knowledge of the object is utilized to eliminate the false positives and improve the extraction precision. As an example of objects in remote sensing images the oil tanks are extracted. Experimental results demonstrate the robustness and effectiveness of the proposed automatic object extraction method.