Comparison of annealing and iterated filters for speckle reduction in SAR
Ian McConnell, Christopher J. Oliver · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
Many of the despeckling filters currently available operate by smoothing over a fixed window, whose size must be decided by two competing factors. Over homogeneous regions large window sizes are needed to improve speckle reduction by averaging. However, a large window size reduces the fundamental resolution of the algorithm, as with multi- looking. For instance, when one of these filters attempt to reconstruct a small bright object it produces artifacts around the object over a distance equal to the filter dimension. This means that the background is badly defined in the neighborhood of bright targets and edges, which is just where one would like it accurate. In this paper, these problems are overcome by introducing a correlated neighborhood model into the MAP filter. This filter operates on a small window and so is able to preserve resolution. The correlation model allows us to describe both the scene heterogeneity and the effects of partial smoothing, which in turn, allows us to iterate the filter, hence, increasing the amount of smoothing that can be achieved with a small window. This gives a filter that is able to adapt to the underlying fluctuations of the scene, preserve detail of still achieve large amounts of smoothing. The final iterated filter is then compared with the current DRA simulated annealing algorithm.