Stochastic matched filtering method applied to SAS imagery

SAS (synthetic aperture sonar) has been used in sea bed imagery. Indeed high resolution images provided by SAS are of great interest, especially for the detection localization and eventually classification of objects lying on sea bed. SAS images are highly corrupted by a granular multiplicative noise, called the speckle which reduces spatial and radiometric resolutions. Most of techniques used consist in the use of multilook processing in range, image-domain filters, adaptive filtering or wavelet-domain filtering. The purpose of this article is to present a new adaptive processing that allows image filtering, for both the additive and multiplicative noise case. This processing is based on the two-dimensional stochastic matched filtering method, which maximize the signal to noise ratio after processing and minimize mean square error between the reconstructed signal and the original one. Experimental results on SAS images are presented and compared to those obtained using some classical approaches.