一种基于多重分形的SAR图像边缘检测方法

分形维数只能刻画那些具有理想的自相似性的分形体,现实中的许多纹理并不满足这一条件,因此单一的分形维数并不足以描述和刻画SAR图像的纹理,多重分形维数更适合于描述图像的纹理.通过计算原始SAR图像离散点数据的奇异性指数,然后对应每一点奇异性指数计算全局多重分形奇异谱,根据判决准则区分边缘和纹理可以实现SAR图像的边缘检测,实验结果表明,基于多重分形特征的边缘检测算法能够检测到许多局部细节,同时又避免出现不重要的细节,突出了主要的边缘信息,很好地区分出SAR图像的纹理和边缘.

SAR image segmentation based on multi-fractal

The texture of SAR images can be described by fractal dimension,but single fractal dimension can not be enough,because fractal dimension can only describe those ideal self-similar fractal object,so multi-fractal is more suitable for describing the texture of images.The discrete image pixels' singularity index of SAR image and global multi-fractal singularity spectrum are calculated out based on multi-fractal principle,and edge extraction is realized by means of edge decision rule.The experimentation showed that this edge detection algorithm based on multi-fractal feature can detect many local details and avoid unessential details,also can distinguish texture and edges of SAR image.