Tham khảo tài liệu 'geoscience and remote sensing, new achievements part 5', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | C-Band Sea Ice SAR Classification Based on Segmentwise Edge Features 133 Sstep Tsz 1 -Tsz 0 Niterations Cstep Tc 0 -Tc 1 Niterations This iteration joins the segments starting from the smaller segments for Niterations do for each segment if segment_size Tsz AND segment_contrast Tc AND some_neighbor_segment_size Tsz then Join the segment to the closest larger segment minimum edge contrast Tsz Tsz Sstep Tc Tc - Cstep endif end end This iteration is just to guarantee that all the segments are joined It typically only has a very small affect if it has . while no changes occur OR maximum count reached do for each segment if segment_size Tsz AND segment_contrast Tc AND some_neighbor_segment_size Tsz then Join the segment to the closest larger segment minimum edge contrast endif end end One way to reduce resolution would also be to reduce the number of clusters K in the K-means clustering . to use less clusters for lower resolutions. We have made some studies of this approach also but the work for finding optimal parametrization and integrating this with the current algorithm is still under construction. Fig. 2. The multi-resolution concept. 3. Edge Features We have used the canny edge detection Canny 1986 to detect edges in the SAR images. The Canny edge detector however only takes into account the local neighborhood in the thresholding. To get the connected edges better included we perform the Canny edge detection twice for one image with two sets of thresholds the high and low thresholds. If an edge resulting 134 Geoscience and Remote Sensing New Achievements Fig. 3. A part of a Radarsat-1 SAR image Baltic Sea 75x75 km upper left and its segmentation in the three resolutions low resolution upper right medium resolution lower left and high resolution lower right . from the Canny edge detection with the high parameter values is connected to an edge detected with the low parameters then the edge from the detection with low parameter values is also included as an edge.
