边缘惩罚层次区域合并SAR图像分割算法
doi: 10.11999/JEIT140331
SAR Image Segmentation Algorithm Using Hierarchical Region Merging with Edge Penalty
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摘要: 该文利用方向边缘强度信息,建立一种新的边缘惩罚SAR图像分割模型,提出一种最小化该模型的层次区域合并算法。利用多方向比例边缘检测算子(MDRED)提取边缘强度信息,并结合分水岭变换获得高质量的初始过分割结果。利用多边形近似区域边缘,提取边缘的方向,将方向边缘强度映射(OESM)融入边缘惩罚中,获得惩罚强度与边缘强度呈反比的惩罚项。逐渐增大边缘惩罚项的强度,获得由图像特征驱动的层次区域合并算法。利用区域邻接图(RAG)表示图像分割,提高区域合并的速度。实验表明:该文方法与其它方法相比在性能和效率上都有优势,获得更好的分割结果。Abstract: A new SAR image segmentation model with edge penalty is constructed, which uses oriented edge strength information and a minimized hierarchical region merging algorithm is proposed in this paper. The edge strength information is extracted by using Multi-Direction Ratio Edge Detector (MDRED), based on which a high quality initial over-segmentation is obtained using watershed transformation. In order to extract the directions of boundaries of regions, polygons are used to approximate them, and a penalty term whose power is in inverse proportion to edge strength is obtained by incorporating Oriented Edge Strength Map (OESM) into the term. A hierarchical region merging algorithm driven by image features is obtained through graduated increased edge penalty. In order to accelerate the region merging, the Region Adjacency Graph (RAG) is used to represent the image segmentation. The experimental results show that the proposed method has advantages in performance and efficiency, and obtains better segmentation results with respect to other methods.
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