针对传统的迭代条件模式(iterated conditional model,ICM)算法应用于遥感影像分割时容易出现离散斑块和孤立点的问题,提出了一种基于马尔科夫随机场(Markov random field,MRF)的改进ICM遥感影像分割算法。首先,在获取初始标记之前加入...针对传统的迭代条件模式(iterated conditional model,ICM)算法应用于遥感影像分割时容易出现离散斑块和孤立点的问题,提出了一种基于马尔科夫随机场(Markov random field,MRF)的改进ICM遥感影像分割算法。首先,在获取初始标记之前加入保边去噪效果良好的双边滤波器(bilateral filter,BF),用于遥感影像的预处理;并用多阈值最大类间方差法(Otsu)获取初始标记,以克服传统的初始标记获取算法中K-means聚类算法类别数不确定和算法复杂度不易控制以及错分现象明显等问题;然后,利用MRF描述像元的空间相关性,形成顾及上下文信息的ICM遥感影像分割算法。通过遥感影像数据分割实例验证,所提方法的分割精度优于传统的ICM算法。展开更多
Traditional image segmentation methods based on MRF converge slowly and require pre-defined weight. These disadvantages are addressed, and a fast segmentation approach based on simple Markov random field （MRF） for S...Traditional image segmentation methods based on MRF converge slowly and require pre-defined weight. These disadvantages are addressed, and a fast segmentation approach based on simple Markov random field （MRF） for SAR image is proposed. The approach is firstly used to perform coarse segmentation in blocks. Then the image is modeled with simple MRF and adaptive variable weighting forms are applied in homogeneous and heterogeneous regions. As a result, the convergent speed is accelerated while the segmentation results in homogeneous regions and boarders are improved. Simulations with synthetic and real SAR images demonstrate the effectiveness of the proposed approach.展开更多
基金supported by the Specialized Research Found for the Doctoral Program of Higher Education (20070699013)the Natural Science Foundation of Shaanxi Province (2006F05)the Aeronautical Science Foundation (05I53076)
文摘Traditional image segmentation methods based on MRF converge slowly and require pre-defined weight. These disadvantages are addressed, and a fast segmentation approach based on simple Markov random field （MRF） for SAR image is proposed. The approach is firstly used to perform coarse segmentation in blocks. Then the image is modeled with simple MRF and adaptive variable weighting forms are applied in homogeneous and heterogeneous regions. As a result, the convergent speed is accelerated while the segmentation results in homogeneous regions and boarders are improved. Simulations with synthetic and real SAR images demonstrate the effectiveness of the proposed approach.
