...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Dictionary-based stochastic expectation-maximization for SAR amplitude probability density function estimation
【24h】

Dictionary-based stochastic expectation-maximization for SAR amplitude probability density function estimation

机译：SAR幅度概率密度函数估计的基于字典的随机期望最大化

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In remotely sensed data analysis, a crucial problem is represented by the need to develop accurate models for the statistics of the pixel intensities. This paper deals with the problem of probability density function (pdf) estimation in the context of synthetic aperture radar (SAR) amplitude data analysis. Several theoretical and heuristic models for the pdfs of SAR data have been proposed in the literature, which have been proved to be effective for different land-cover typologies, thus making the choice of a single optimal parametric pdf a hard task, especially when dealing with heterogeneous SAR data. In this paper, an innovative estimation algorithm is described, which faces such a problem by adopting a finite mixture model for the amplitude pdf, with mixture components belonging to a given dictionary of SAR-specific pdfs. The proposed method automatically integrates the procedures of selection of the optimal model for each component, of parameter estimation, and of optimization of the number of components by combining the stochastic expectation-maximization iterative methodology with the recently developed "method-of-log-cumulants" for parametric pdf estimation in the case of nonnegative random variables. Experimental results on several real SAR images are reported, showing that the proposed method accurately models the statistics of SAR amplitude data.
机译：在遥感数据分析中，关键问题是需要开发精确的像素强度统计模型。在合成孔径雷达（SAR）幅度数据分析的背景下，本文讨论了概率密度函数（pdf）估计的问题。文献中提出了几种SAR数据pdf的理论和启发式模型，这些模型已被证明对不同的土地覆盖类型有效，因此，选择单个最佳参数pdf成为一项艰巨的任务，尤其是在处理异构SAR数据。在本文中，描述了一种创新的估计算法，该算法通过对幅度pdf采用有限混合模型来解决该问题，其中混合分量属于给定的SAR特定pdf字典。所提出的方法通过将随机期望最大化迭代方法与最近开发的“对数累积量方法”相结合，自动集成了针对每个组件的最佳模型的选择，参数估计以及对组件数量的优化的过程。对于非负随机变量的参数pdf估计。报道了在多个真实SAR图像上的实验结果，表明该方法可以准确地对SAR振幅数据的统计进行建模。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号