A High-Efficiency Automatic <inline-formula> <tex-math notation='LaTeX'>$U$ </tex-math></inline-formula>-Distribution Segmentation Algorithm for PolSAR Images

Hu Dingsheng; Doulgeris Anthony P.; Qiu Xiaolan; Lei Bin; Jin Yan

首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >A High-Efficiency Automatic

$U$

-Distribution Segmentation Algorithm for PolSAR Images

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A High-Efficiency Automatic $U$ -Distribution Segmentation Algorithm for PolSAR Images

机译：高效自动 $ U $ PolSAR图像的分割分段算法

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摘要

A fully automatic, non-Gaussian, and contextual clustering algorithm for segmentation of polarimetric synthetic aperture radar (SAR) images has been previously presented by Doulgeris. It achieved good results for both simulated and actual data sets. However, the long computation time was its main drawback. This letter discusses modifications to improve computational efficiency. The primary speed issues were rooted in the complicated probability density function (PDF) of the adopted model, for which evaluating the posterior probability of samples and estimating the parameters were both very time-consuming. We investigate the model parameters, reparametrize the model, and introduce lookup tables to speed up the processing chain. The new strategy speeds up both PDF evaluation and parameter estimation while maintaining the exactly similar visual results and now makes advanced non-Gaussian SAR image analysis a practical alternative.

机译：荷尼尔州以前提出了一种全自动，非高斯和上下文和上下文聚类算法，用于Polarimetric合成孔径雷达（SAR）图像的分割。它对模拟和实际数据集实现了良好的结果。然而，长的计算时间是其主要缺点。这封信讨论了改进计算效率的修改。初级速度问题源于所采用模型的复杂概率密度函数（PDF）中，用于评估样品的后验概率并估计参数既非常耗时。我们调查模型参数，重新处理模型，并引入查找表以加快处理链。新策略加速了PDF评估和参数估计，同时保持了完全相似的视觉结果，现在使先进的非高斯SAR图像分析成为实际的替代方案。

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来源
《IEEE Geoscience and Remote Sensing Letters》 |2019年第5期|831-835|共5页
作者
Hu Dingsheng; Doulgeris Anthony P.; Qiu Xiaolan; Lei Bin; Jin Yan;
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作者单位

Chinese Acad Sci Inst Elect Beijing 100190 Peoples R China|Univ Chinese Acad Sci Beijing 100049 Peoples R China;

UiT Arctic Univ Norway Dept Phys & Technol N-9037 Tromso Norway;

Chinese Acad Sci Inst Elect Beijing 100190 Peoples R China;

Chinese Acad Sci Inst Elect Beijing 100190 Peoples R China;

Chinese Acad Sci Inst Elect Beijing 100190 Peoples R China;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Efficiency improvement; polarimetric synthetic aperture radar (PolSAR); segmentation; statistic model;

机译：效率改进;Polariemetric合成孔径雷达（POLSAR）;分割;统计模型;

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专利

1. A High-Efficiency Automatic $U$ -Distribution Segmentation Algorithm for PolSAR Images [J] . Hu Dingsheng, Doulgeris Anthony P., Qiu Xiaolan, IEEE Geoscience and Remote Sensing Letters . 2019,第5期

机译：PolSAR图像的高效自动 $ U $ -分布分割算法
2. Closed-Loop d${bm i}/$d ${bm t}$ and d ${bm v}/$d${bm t}$ IGBT Gate Driver [J] . Lobsiger Y., Kolar J.W. Power Electronics, IEEE Transactions on . 2015,第6期

机译：闭环d $ {bm i} / $ d $ {bm t} $ 和d $ {bm v} / $ d $ {bm t} $ IGBT栅极驱动器
3. An Automatic ${cal U}$-Distribution and Markov Random Field Segmentation Algorithm for PolSAR Images [J] . Doulgeris A.P. Geoscience and Remote Sensing, IEEE Transactions on . 2015,第4期

机译：PolSAR图像的自动 $ {cal U} $ -分布和马尔可夫随机场分割算法
4. A fast automatic U-distribution segmentation algorithm for polsar images [C] . Dingsheng Hu, Anthony P. Doulgeris, Xiaolan Qiu, IEEE International Geoscience and Remote Sensing Symposium . 2016

机译：polsar图像的快速自动U分布分割算法
5. Automatic Liver and Tumor Segmentation from CT Scan Images using Gabor Feature and Machine Learning Algorithms [D] . Shrestha, Ujjwal. 2018

机译：使用Gabor特征和机器学习算法从CT扫描图像自动进行肝脏和肿瘤分割
6. Automatic Segmentation of Ground-Glass Opacities in Lung CT Images by Using Markov Random Field-Based Algorithms [O] . Yanjie Zhu, Yongqing Tan, Yanqing Hua, 2012

机译：基于马尔可夫随机场的算法自动分割肺部CT图像中的玻璃不透明度
7. Physical-Layer Security for Mixed $eta$ – $mu$ and $mathcal {M}$ -Distribution Dual-Hop RF/FSO Systems [O] . Liang Yang, Ting Liu, Jianchao Chen, 2018

机译：混合 $ eta $ - $ mu $ 和 $ mathcal {m} $ - 分配双跳RF / FSO系统

A High-Efficiency Automatic $U$ -Distribution Segmentation Algorithm for PolSAR Images

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