Data sewing algorithm for parallel segmentation of high-resolution remotely sensed image
高分辨率遥感影像并行分割结果缝合算法

In the process and analysis of high-resolution remote sensing image, segmentation is the key step of extracting information from image data to image object. For the image segmentation tasks of large amount of data, data paralleled computing model is generally used. In this process, the effect of merging segmentation results when data gathering is related to the precision and accuracy of the subsequent object-oriented analysis. In this paper, data paralleled segmentation of remote sensing image is adopted, and a new algorithm named data sewing is proposed to solve the problem of merging segmentation results. Experi-ments, such as comparison of final segmentation results and assessment of computing efficiency, show that the algorithm im-proves the efficiency of image segmentation process. Meanwhile it guarantees the correctness of the boundary thus to ensure the credibility of the final segmentation result as well.