中文摘要：

合成孔径雷达（SAR）海冰图像的精确分割是准确解译海冰分布信息的前提,但现有分割方法受相干斑噪声影响严重,分割误差大,解译结果可靠性低。提出一种基于低秩稀疏表示的SAR海冰图像分割方法,首先利用噪声分布的稀疏性,通过鲁棒性主成分分析提取图像的稀疏分量,再利用双边滤波增强图像细节信息。针对基于固定势函数的MRF分割模型无法准确反映图像区域间关联性的问题,根据贝叶斯置信传播算法建立基于交互势函数的MRF分割模型准确分割海冰图像。利用Radarsat系列卫星数据验证算法性能,结果表明：和传统算法相比,本文算法在保持分割图像连通性的同时,能增强图像的细节信息,具有更高的分割精度。

英文摘要：

Accurate segmentation of Synthetic Aperture Radar（SAR）images is the premise of interpreting the distribution information of sea ice.However the existing segmentation methodsare seriously interfered by speckle noise,which leads to high segmentation error and low reliability interpreting results.In this paper,a novel sea ice SAR image segmentation method based on low rank sparse representation is proposed,firstly sparse components are extracted from the source image by using robust principal component,and then bilateral filter is used to enhance the image details.Due to the MRF segmentation model based on fixed potential function cannot accurately reflect the relevance between the areas,MRF segmentation model based on interactive potential function is built to segment the sea ice image accurately.A series of Radarsat satellites data are tested to validate performance of the proposed method,the results show that compare with traditional segmentation algorithms,the proposed method algorithm can not only maintain the connectivity of the image better,but also has higher segmentation accuracy.