Fractal-Based Segmentation For SAR Images

Synthetic Aperture Radar (SAR) plays an important role in modern remote sensing. It was broadly applied in almost every field of economy and society sustainable development because of its capability of providing all weather, full-time information about the earth. SAR images are very different from the visual or infrared images commonly used in remote sensing. The primary difficulties of SAR image processing and analysis lie both on that the interaction between electromagnetic wave and ground objects have not been revealed completely and that SAR image is subject to Speckle phenomenon which disturb the interpret of SAR images. The traditional digital image processing and analysis techniques based on grayscale that work successfully on nature images often do not perform as well on SAR images. With the rapid growth of available SAR data, the development of SAR image understanding techniques was desired. SAR image interpretation is now the urgent issue of remote sensing and computer vision.Segmentation of SAR image based on texture is a critical preliminary operation in various SAR image processing application. This thesis focuses on the region segmentation of SAR images based on fractal method .The method is realized by exploiting the fractal dimension as the texture feature combined with edge character and iterative filter on the basis of the characteristics of the SAR images. Besides, an edge detection algorithm based on A/G coefficient is elaborated for improving efficiency of region edge detection, it affords a good edge character for region segmentation.In the end of this paper we give some experiment results of synthetic images and real SAR images that show fractal method proposed is effective.