부산대학교 도서관

The characteristics of remote sensing image is not obvious and can not reflect the be reconstructed the detail characters of the objects. For the sparse points in multi images fusion results, texture selection and it is relatively difficult problems, for accurate reconstruction of remote sensing image details, this paper presents CMVS-PMVS(cluster multi view stereo- patch based multi view stereo) combining with region growing for computing dense matching points. First, select some seed points by region growing algorithm, and find the matching relationship between the seed points, followed by the matching relation from the seed point to spread until to the entire image. Then the image set are clustered by CMVS in order to reduce the amount of data in the process of reconstruction, and the operation rate and reconstruction accuracy can be improved. PMVS reconstruction method is used to complete the reconstruction task by matching, expanding and filtering three steps. The experimental results showed that the point cloud is dense enough which are reconstructed by the 3d reconstruction algorithm based on regional growth combining CMVS-PMVS and well expressed the practical model of object reconstruction, the reconstruction of objects in remote sensing images has very strong practicability.