【作者】 李武周；

【导师】 库锡树；

【作者基本信息】 国防科学技术大学 ， 电子科学与技术， 2010， 硕士

【摘要】 合成孔径雷达(Synthetic Aperture Radar,SAR)图像分割的目的是从复杂的地物场景中提取和识别特定的目标。基于马尔可夫随机场(Markov Random field, MRF)模型的图像分割方法能够将标记图像的上下文信息和待分割图像的统计特性统一起来,特别适合SAR图像的分割,因此开展相关研究工作十分有必要。论文以马尔可夫随机场理论为研究基础,系统归纳和总结了国内外研究成果和经验,按照SAR图像分割方法的基本步骤展开。论文的主要工作有:(1)论述了在SAR图像分割中引入MRF模型的优点,并阐述了MRF模型的原理和方法;(2)在参阅大量文献的基础上,总结了各种已有的杂波统计模型。重点介绍了乘积模型中的K分布模型和G~0分布模型;(3)在总结杂波统计模型的基础上,给出了各种参数模型的参数估计方法。着重介绍了G~0分布的参数估计方法,并在已有方法的基础上提出了一种Mellin变换和矩估计相结合参数估计方法;(4)总结了各类MRF模型求最优解的迭代算法,对各种迭代算法的特点进行了分析,并对其中的典型算法进行仿真比较;(5)通过优化MRF模型的邻域结构,引入了一种具有图像细节保护能力的自适应邻域结构的SAR图像分割方法,并利用合成SAR图像和真实SAR图像与传统MRF模型的分割结果进行对比分析,结果表明,该分割方法可以较好的保留图像细节。更多还原

【Abstract】 The aim of Synthetic Aperture Radar (SAR) images segmentation is extracting and detecting specific targets from complex ground scene. The segmentation methods of images based on Markov Random Field (MRF) model able to unify the contextual information from label images and statistical properties of observed images, which are especially suitable for segmentation of SAR images. Therefore, developing a relevant research work on this field is necessary.In this paper, we start our works according to the basic steps of SAR images segmentation based on MRF theory, also concluded and summarized research works and experiences at home and abroad. The work of this paper can be concluded as follows:(1) Discussed the advantages that introduce MRF model to SAR images segmentation, and described the principles and methods of MRF model;(2) Summarized all kinds of existing clutter statistical models based on reading extensive literatures, K distribution model and G~0 distribution model are our focuses;(3) Summarized parameter estimation methods of existing clutter statistical models, introduced G~0 distribution model parameter estimation methods emphatically, then proposed a new parameter estimation method which combines the methods of moments and the method based on Mellin transform on the basis of existing G~0 distribution model parameter estimation methods.(4) Summarized the various types of existing iterative algorithms of MRF model, and analyzed the characteristics of existing iterative algorithms, then some typical algorithms are simulated and compared;(5) Introduced a new SAR images segmentation method with details preserving ability based on adaptive neighborhoods by optimizing the neighborhoods structure of MRF model. We use synthetic and real SAR images to compare the segmentation results, the results show that the segmentation method can preserve image details better.更多还原