Fast segmentation method of high-resolution remote sensing image

In recent years, C-V model has been extensively used in image segmentation, but the computation speed is the key factor restricting the use of the method, especially for the large high resolution remote sensing imagery with complex scene, since the consuming time is very long. This research presented the method of combining C-V model and wavelet transform, which not only can improve the speed but also can achieve the multi-resolution segmentation, and has good anti-noise performance. Experiment results show that our method can improve the speed 1-2 times compared to the C-V model in the premise of segmentation quality assurance.