Choosing weight functions for filtering SAR

Abstract

One of the biggest problems in automatic processing of synthetic aperture radar (SAR) imagery is the large amount of noise due to speckle. Some form of smoothing is needed before interpretation can take place. Traditionally, the amount of smoothing has been chosen in an arbitrary manner. Optimal smoothing filters, such as the Wiener filter, may be derived, but their implementation is a demanding task in most image handling systems. This paper suggests that by constraining image autocorrelations and smoothing filter weights to be functions with few parameters, a useful saving in the complexity of algorithms may be achieved, with little loss of filter performance. It is also shown that the performance of this approach is robust to the form of the autocorrelation function.