基于结构保持MRF模型的SAR图像去斑
doi: 10.3724/SP.J.1146.2007.01645
A Novel MRF Model for Structure Preservation in SAR Image Despeckling
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摘要: 该文提出一种用于SAR图像贝叶斯去斑的，具有结构保持特性的马尔可夫随机场模型。该模型通过引入一组权重参数建模待处理像素与其邻域点的空间相关性，可有效描述图像中的各种局部特性。准确的参数估计是模型有效运用的关键，借鉴随机松弛算法的思想，通过引入温度变量，实现了迭代过程中权重参数的自适应估计。仿真和实际SAR图像数据的实验结果，验证了所提模型及参数估计方法的有效性。Abstract: A novel MRF model called SPMRF (Structure Preserving MRF) is proposed for Bayesian despeckling of SAR images. In SPMRF every pixel within a neighborhood is associated with a weighting parameter which determines its contribution to the central pixels despeckling. And a temperature variable is introduced into SPMRF to control the weighting parameters estimating process which makes the model match with images local characteristics better. Experiments show as a prior model SPMRF can retain image structures efficiently with despeckling progressing.
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