Abstract

An imaging radar generates a SAR image by transmitting a coherent electromagnetic wave and subsequently processing the backscattered signal from the illuminated objects. However, due to interference processes between scatterers, speckle noise is introduced into the image. Speckle noise is a disturbing factor because it limits the ability to correctly interpret SAR images, restricts edge extraction, image segmentation, target recognition and classification, and it introduces uncertainty in ground surface parametric inversion. Therefore, it is important to apply suitable speckle reduction methods prior to the image processing, which are able to smooth speckle noise, while retaining as much detailed information as possible. There are two types of speckle noise reduction techniques:

Multi-look processing, which involves the incoherent averaging of multiple looks of the same scene during the generation of the SAR image. This process narrows down the probability density function of the speckle noise and reduces the variance, but it also reduces the spatial resolution and improves the radiometric resolution. This simple technique is able to remove speckle noise efficiently, but much of the edge information is lost [3].

Spatial filtering, which is performed on the image domain and involves an analysis of the local statistics of each pixel.