The DRA despeckling algorithm

We present an algorithm that is able to smooth out the speckle from many different kinds of SAR images and which does not suffer from the drawbacks of multilooking. The algorithm is able to preserve the detail and resolution of the original image while producing a smooth, real valued output. In many cases the quality of the smoothed image is sufficiently high that it may be used with standard optical post-processing algorithms. This work extends an earlier despeckler that used a gaussian model to the more appropriate gamma statistics. It was found that by using the correct model for the data we achieved major improvements, both in the quality of the resultant image and in the execution speed. The current algorithm uses a global optimization method (The Taboo Search) and maximum likelihood estimates to find the MAP solution for the radar cross-section. However, this method may also be regarded as an ideal adaptive filter that is both computationally efficient and highly parallelizable. The algorithm successfully despeckles many different types of scene from both airborne and spaceborne SAR systems and is also able to use multi-temporal images to produce an improved set of despeckled images