Filtering of radar images based on blind evaluation of noise characteristics
Владимир Васильевич Лукин, Nikolay N. Ponomarenko, Sergey Abramov, Benoît Vozel, Kacem Chehdi, Jaakko T. Astola · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
A common assumption concerning noise in radar images is that it is of multiplicative nature and spatially uncorrelated. Meanwhile, recent studies have shown that additive noise component cannot be neglected, especially for images formed by side look aperture radars (SLARs). Moreover, majority of radar image filtering techniques are designed under assumption that noise is i.i.d., i.e. spatially uncorrelated. However, in many practical situations the latter assumption is not true. Besides, spatial correlation properties of noise can be different and they are often a priori unknown. In this paper we demonstrate that complex statistical and spatial correlation characteristics of noise in radar images can and should be taken into consideration at image filtering stage. We design a modification of the denoising algorithm based on discrete cosine transform (DCT) that is able to easily incorporate a priori information or obtained estimates of noise statistical and spatial correlation characteristics. This can be done in automatic (blind) manner due to utilizing a sequence of blind estimation operations. We present simulation results that show appropriate accuracy and robustness of these operations. Finally, real life image filtering examples are given that confirm the effectiveness of the designed techniques.