بررسي فيلترهاي كاهش نويز لكه اي در تصاوير رادار با گشودگي تركيبي براي مناطق جنگلي شمال ايران

Investigation of De-Speckling Filters in SAR images for Forest areas in North of Iran

One of the major factors plaguing the performance of Synthetic Aperture Radar (SAR) imagery is the presence of signal-dependent speckle noise. Grainy in appearance, speckle noise is primarily due to the phase fluctuations of the electromagnetic return signals. In this paper, we will investigate six de-speckling filters: Frost, Kuan, Lee, Enhanced Frost, Enhanced Lee and Gamma on a JERS-1 image for north of Iran in Gilan. Texture information is an important parameter to analyzing the forested areas, also the texture and variety of forest covers is various in different areas, therefore it is important to investigate and choose a suitable de-speckling filter for different areas. This paper try to find suitable filter for a forestry area contains trees such as Alnus, zelkova carpinifolia, fagus orientalis, carpinus betulus. Performance of an algorithm to remove noise and retrieve primary image is based on preservation useful information of image texture and edges. The ratio images show that the Gamma, Enhanced Lee, Lee, Kuan, Enhanced Frost and finally Frost filter have better performance to reserve edges and texture of image after noise removing. Results show that the filters with the means near to one and less standard deviation have reserved the edge information better than other. In this paper, we will show the Enhanced Lee filter have the best performance for the studied forestry area.