The simulated annealing (SA) algorithm , originally developed by White R G for speckle reduction of synthetic aperture radar (SAR) images, shows significant improvement on the reconstruction of both homogeneous and ...The simulated annealing (SA) algorithm , originally developed by White R G for speckle reduction of synthetic aperture radar (SAR) images, shows significant improvement on the reconstruction of both homogeneous and strong structured areas. But his algorithm also has drawbacks itself, especially over smooth thin and weak textures and structures. In this study, a modified version of the algorithm is presented. The SA approach is extended to incorporate an edge detection and enhancement step that makes thin and weak structures strong enough to be preserved during annealing. To cooperate with this method, a temperature steadily decreased exponential schedule is adopted instead of the logarithm plan. By delicately adjusting the SA process, the proposed approach can well preserve many fine features in an SAR image while not degrading performance of other scenes such as homogeneous and strong structured areas and without other additional image defects. This feature makes the algorithm more suitable for filtering low and medium resolution SAR images.展开更多
文摘The simulated annealing (SA) algorithm , originally developed by White R G for speckle reduction of synthetic aperture radar (SAR) images, shows significant improvement on the reconstruction of both homogeneous and strong structured areas. But his algorithm also has drawbacks itself, especially over smooth thin and weak textures and structures. In this study, a modified version of the algorithm is presented. The SA approach is extended to incorporate an edge detection and enhancement step that makes thin and weak structures strong enough to be preserved during annealing. To cooperate with this method, a temperature steadily decreased exponential schedule is adopted instead of the logarithm plan. By delicately adjusting the SA process, the proposed approach can well preserve many fine features in an SAR image while not degrading performance of other scenes such as homogeneous and strong structured areas and without other additional image defects. This feature makes the algorithm more suitable for filtering low and medium resolution SAR images.
