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. Experiments

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.