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- Abstract： In this paper, a new method of speckle reduction in polarimetric SAR image is proposed. 摘 要： 提出了一种新的极化SAR图像相干斑抑制的方法。
- In this paper, a new method of speckle reduction in polarimetric SAR image is proposed. 提出了一种新的极化SAR图像相干斑抑制的方法。
- This parameter can be employed for ship detection and bridge detection from a polarimetric SAR image. 该参数能在河流区域很好地进行舰船检测与桥梁检测。
- The effectiveness of this method is demonstrated using an L-band fully polarimetric SAR image of San Francisco, acquired by the NASA/JPL AIRSAR sensor. NASA/JPL实验室AIRSAR系统获取的L波段旧金山全极化SAR数据的实验结果验证了该文方法的有效性。
- The experiment shows ICA algorithm can separate speckle from polarimetric SAR image effectively and improve the performance of the image. 同时独立分量分析算法实现比较简单,计算方便有效。
- Experiment is performed on a L-band NASA/JPL SIR-C polarimetric SAR image over Danshui town, Guangdong, P.R.China.Furthermore, the movements of the clustering centers are discussed. 以中国广东淡水附近的L波段NASA/JPL SIR-C全极化SAR图像作为实验数据进行了仿真试验，并进一步对聚类中心的迁移进行了讨论。
- multifrequency polarimetric SAR image 多频极化SAR图像
- A new feature selection algorithm is presented using SVM, and then it is integrated into the classification procedure of polarimetric SAR images to construct a novel SVM-based classification method. 该文提出一种新的利用SVM的特征选择算法，并将其融入到极化SAR图像分类过程中，构成一种新的基于SVM的分类方法。
- In this paper, SVM is used in classification of polarimetric SAR images based on feature extraction, and effect of several important parameters of SVM on classification performance is analyzed. 该文在极化SAR特征提取的基础上，将SVM应用于极化SAR图像分类，分析了分类器参数对分类性能的影响。
- Ship Detection Algorithm in Polarimetric SAR Images 极化合成孔径雷达图像船舶目标检测算法
- Classification of Polarimetric SAR Image Based on Cameron Decomposition and SVM 基于Cameron分解和SVM的极化SAR图像分类
- Unsupervised Classification of Polarimetric SAR Image Using Deorientation Theory and Complex Wishart Distribution 基于去取向理论的全极化SAR图像模糊非监督聚类
- The Iteration Classification Method and Experiment Study Based on Unsupervised Classification of Fully Polarimetric SAR Image 基于全极化SAR非监督分类的迭代分类方法
- fully polarimetric SAR image 全极化SAR图像
- polarimetric SAR image 极化合成孔径雷达图像
- Unsupervised Classification Methods and Experimental Research of Dual-frequency Fully Polarimetric SAR Images 双波段全极化SAR图像非监督分类方法及实验研究
- Coherent Matrix Eigenvalue and Eigenvalue Index of Polarimetric SAR Images and its Appliction of Bayes Classification 全极化SAR图像中相干矩阵特征值及其应用
- In the process of designing a spaceborne polarimetric SAR system it is required to restrain the system ambiguity and improve the image quality effectively. 现有的多极化SAR系统极化时分工作方式虽然简单易行,但在高轨道星载条件下系统的距离模糊问题变得十分严重。
- The validity of the novel method is indicated by experimental results with fully polarimetric SAR data sets. 利用全极化SAR实测数据验证了该文方法的优良性能。
- Finally, the paper shows the polarimetric SAR three dimensional images from authentic data. 并利用真实的极化 SAR图像数据得到了极化三维成像结果。
