Speckle reduction in multipolarization, multifrequency SAR imagery

An algorithm to take advantage of this polarization diversity to suppress the speckle effect with much less resolution broadening than using spatial filtering is discussed. The coupling between polarization channels is minimized by using local intensity ratios. The degree of speckle reduction is similar to two-look or three-look processing. The same algorithm can also be used to process multifrequency polarimetric SAR. For three-frequency aircraft SAR data speckle reduction equivalent to six-look processing can be achieved. Further speckle reduction is possible by applying speckle filters in the spatial domain. In addition, a vector speckle filter which operates simultaneously in the polarization and spatial domains is tested. Experimental results with simulated polarimetric SAR as well as one-look and multilook parametric SAR data demonstrate the effectiveness of these speckle reductions, with minimum resolution broadening and coupling between polarimetric and frequency channels. Comparisons with other algorithms are also made     

基于差异度的极化SAR相干斑抑制效果评估

相干斑抑制是极化SAR图像解译和信息提取的基础。针对采用极化特征图对极化SAR图像相干斑抑制算法极化信息保持能力定性评估的不足,本文提出一种基于差异度的相干斑抑制效果评估方法。该方法通过比较相干斑抑制前后目标区域的差异度,实现相干斑抑制算法对目标极化信息保持能力的定量评估。在评估过程中采用分别先对目标区域内每个像素做差异度后求平均的方法,代替传统的先将目标区域内像素K矩阵求平均后求极化特征图的方法,避免了先对各个像素做平均带来的二次估计。对通过极化特征图判断性能接近的不同相干斑抑制算法,得到更为精确的评估结果。最后选取三类典型相干斑抑制算法,分别对仿真数据和实测ESAR数据中的面目标和点目标进行评估,验证了方法的有效性。      

Study on speckle reduction in multi-look polarimetric SAR image

This paper studies the speckle reduction in multi-look polarimetric synthetic aperture radar (SAR) image. A multi-look polarimetric whitening filtering (MPWF) method is presented and extended to form a fully polarimetric filter with multi-channel output. The paper also quantifies the speckle reduction amount achievable by the MPWF, and compares the MPWF with the span, weighting and power equalization methods. Experimental results with the NASA/JPL L-band 4-look polarimetric SAR data verify the effectiveness and superiority of the MPWF, and show that the MPWF is of great advantage for enhancing SAR image classification.     

多视极化SAR图象相干斑抑制的研究

本文研究多视极化合成孔径雷达(SAR)图象的相干斑抑制,提出多视极化白化滤波(MPWF)法,并进一步将它发展成具有多通道输出的全极化滤波器。本文还定量地分析了MPWF方法抑制相干斑的能力,并在理论上同全功率法、加权法和功率均衡法进行了比较。应用NASA/JPL机载L波段四视全极化SAR数据的试验结果验证了所提方法的有效性和优越性,也说明了MPWF处理能显著地提高SAR图象的分类精度。     

一种新的极化滤波综合性能评估方法

极化合成孔径雷达(SAR)可以获得目标散射的相位信息,这种更加丰富的信息为极化SAR图像相干斑噪声抑制提供了更好的解决方法。通过对几种典型的极化滤波技术的算法实现,基于采样信号波形图、极化特征图和相对标准差,提出了一种新的极化滤波综合性能评估方法。对实测极化SAR数据进行实验验证,结果表明局部统计滤波在图像分辨率的保持、极化信息的保留和相干斑噪声的抑制3个方面都有很好的效果。     

An Improved SAR Image Denoising Metho d Based on Bo otstrap Statistical Estimation with ICA Basis

A new method for Synthetic aperture radar (SAR) image denoising is proposed. The prior information of speckle statistical model can be exploited to judge its distribution. The basis of SAR image can be estimated by Independent component analysis (ICA), and these bases can be divided into two different subspaces (noise and real signal subspaces) through a linear classifier. Then para-metric Bootstrap estimates the parameters of speckle sta-tistical model on the noise signal subspace, and the non-parametric Bootstrap can estimate the distribution of real image on the real signal subspace. According to different results estimated by Bootstrap, corresponding Maximum a posterior probability (MAP) filter will be selected for im-age denoising, using the noise model’s parameter for adap-tive filtering. Experiments show that the image processed by this new method can achieve a better visual perception and ob jective evaluation results.     

基于ICA-SCS算法的极化SAR图像相干斑抑制

该文提出了采用基于独立分量分析的稀疏编码收缩(ICA-SCS)算法进行极化SAR图像相干斑抑制的新方法,结合软门限算子,有效抑制了图像中的相干斑噪声,保留了极化信息。实验结果表明,该算法具有较好的边缘保持和噪声抑制能力。     

用一种新的独立分量分析算法实现极化SAR图像相干斑抑制

极化SAR图像为雷达图像中的信息处理和获取提供了更为便捷的途径。本文在研究极化SAR成像特点的基础上，介绍了用一种新的独立分量分析(ICA)方法—Infomax算法来进行相干斑抑制，完成了从极化SAR图像中分离相干斑噪声的仿真试验。实验表明，Infomax算法收敛速度较慢，但稳健性好。经ICA处理后的图像其相干斑噪声得到了有效的抑制，具有较低的相干斑指数，明显地改善了图像的质量。     

基于同质像素预选择的极化SAR图像非局部均值滤波

该文针对在极化合成孔径雷达(PolSAR)图像相干斑抑制过程中结构特征和极化散射特性保持的难题,提出一种基于同质像素预选择的非局部均值滤波算法(NLM-HPP)。该算法结合像素统计特性和极化散射机制选择滤波同质像素,并引入结构损失函数提高非局部均值(NLM)算法中像素间相似性度量的准确性,最后用改进的相似性度量对同质像素的协方差矩阵进行加权平均,实现对PolSAR图像的相干斑抑制。对真实PolSAR数据进行的实验结果表明,与现有的Refined Lee滤波、基于散射模型的滤波方法和两种非局部均值滤波相比,此方法在有效滤除相干斑点的同时能更好地保持PolSAR图像的结构信息和极化信息。     

结构保持的双边滤波极化SAR图像降噪

针对极化合成孔径雷达(Polarimetric Synthetic Aperture Radar, PolSAR)图像相干斑抑制时结构保持的难题,该文提出一种PolSAR图像的双边滤波算法:结构保持的双边滤波(SPBF)。该算法通过结合边缘结构特征和地物散射特性,增强对PolSAR图像结构信息的描述,减少滤波时图像结构信息的损失,实现滤波性能的提高。该算法首先使用边缘检测模板在极化总功率图像(Span)上提取边缘方向,实现自适应选择滤波方向窗;其次,采用Freeman-Durden分解获取像素的散射机制,并根据极化数据的统计分布特性获取地物散射的聚类标记;最终在所选的方向窗中,以聚类标记图为掩膜,利用改进的双边滤波算法对PolSAR数据进行相干斑抑制。真实SAR数据的实验结果表明,该方法能够有效抑制相干斑噪声,同时提高了对图像的边缘、强点目标和极化散射特性的保持能力。     

The fast fixed-point algorithm for speckle reduction of polarimetric SAR image

In this letter, a simple and efficient method of image speckle reduction for polarimetric SAR is put forward. It is based on the fast fixed-polnt ICA (Independent Component Analysis) algorithm of orthogonal and symmetric matrix. Simulation experiment is carried out to separate speckle noise from the polarimetric SAR images, and it indicates that this algorithm has high convergency speed and stability, the image speckle noise is reduced effectively and the speckle index is low. and the image quality is improved obviously.     

多极化SAR图像的降斑研究

对于多极化SAR图像,可以利用其同极化和交叉极化图像的相关性来进行降斑处理.本文对常用的几种基于多极化SAR图像的降斑方法进行了分析,重点研究了最优加权法(the optimal weighting algorithm),在其基础上改进提出了分块加权法,取得了明显的降斑效果,并较大地减少了运算量.最后利用实测的SAR数据进行了验证.     

全极化合成孔径雷达多视图像的极化特征分析

该文基于乘性相干斑模型,对全极化合成孔径雷达多视图像的极化特征参数(同极化比、交叉极化比和同极化相位差)进行了分析,利用实际的模拟数据对特征参数的PDF进行了拟合测试,分析了多视极化特征参数的统计特性对极化相干斑抑制算法的影响。利用极化比和相位差的特点,对地物进行分类,所得分类精度与利用最优极化分类法的分类精度具有可比性。     

Fractional Brownian motion models for synthetic aperture radarimagery scene segmentation

The application of fractal random process models and their related scaling parameters as features in the analysis and segmentation of clutter in high-resolution, polarimetric synthetic aperture radar (SAR) imagery is demonstrated. Specifically, the fractal dimension of natural clutter sources, such as grass and trees, is computed and used as a texture feature for a Bayesian classifier. The SAR shadows are segmented in a separate manner using the original backscatter power as a discriminant. The proposed segmentation process yields a three-class segmentation map for the scenes considered in this study (with three clutter types: shadows, trees, and grass). The difficulty of computing texture metrics in high-speckle SAR imagery is addressed. In particular, a two-step preprocessing approach consisting of polarimetric minimum speckle filtering followed by noncoherent spatial averaging is used. The relevance of the resulting segmentation maps to constant-false-alarm-rate (CFAR) radar target detection techniques is discussed     

超高分辨率PolSAR图像去噪对极化特征的影响

随着超高分辨率极化合成孔径雷达(PolSAR)图像数据的出现,有必要对PolSAR图像的去噪过程对于极化分解结果的影响进行评测。相干斑去噪过程的实施将对观测场景中的PolSAR图像原有极化属性产生不同程度的影响,这将会导致分解结果出现偏差。以非相干分解模型为评估对象,以喷气推进实验室(JPL)提供的开源机载超高分辨率PolSAR系统数据为实验样本,提出了一种利用绝对相对误差的定量评测方法。评测结果显示：对于超高分辨率图像,相干斑噪声的影响明显变小,分解窗口可相应的缩小为7×7的尺寸。研究结果对于PolSAR图像的后期遥感应用中的参数选择具有重要参考意义。     

CFAR edge detector for polarimetric SAR images

Finding the edges between different regions in an image is one of the fundamental steps of image analysis, and several edge detectors suitable for the special statistics of synthetic aperture radar (SAR) intensity images have previously been developed. In this paper, a new edge detector for polarimetric SAR images is presented using a newly developed test statistic in the complex Wishart distribution to test for equality of covariance matrices. The new edge detector can be applied to a wide range of SAR data from single-channel intensity data to multifrequency and/or multitemporal polarimetric SAR data. By simply changing the parameters characterizing the test statistic according to the applied SAR data, constant false-alarm rate detection is always obtained. An adaptive filtering scheme is presented, and the distributions of the detector are verified using simulated polarimetric SAR images. Using SAR data from the Danish airborne polarimetric SAR, EMISAR, it is demonstrated that superior edge detection results are obtained using polarimetric and/or multifrequency data compared to using only intensity data.     

Unsupervised segmentation of polarimetric SAR data using thecovariance matrix

A method for unsupervised segmentation of polarimetric synthetic aperture radar (SAR) data into classes of homogeneous microwave polarimetric backscatter characteristics is presented. Classes of polarimetric backscatter are selected on the basis of a multidimensional fuzzy clustering of the logarithm of the parameters composing the polarimetric covariance matrix. The clustering procedure uses both polarimetric amplitude and phase information, is adapted to the presence of image speckle, and does not require an arbitrary weighting of the different polarimetric channels; it also provides a partitioning of each data sample used for clustering into multiple clusters. Given the classes of polarimetric backscatter, the entire image is classified using a maximum a posteriori polarimetric classifier. Four-look polarimetric SAR complex data of lava flows and of sea ice acquired by the NASA/JPL airborne polarimetric radar (AIRSAR) are segmented using this technique     

基于双边滤波的极化SAR 相干斑抑制

在对极化SAR 数据进行相干斑抑制过程中,保持其极化信息是首要考虑的问题,而对极化SAR 数据各元素进行独立的滤波是不可取。依据极化SAR 数据形式及噪声模型,该文将双边滤波推广至极化SAR 数据处理,推导出一种新的相似性距离度量公式,所提方法可以直接对极化协方差矩阵C 或极化相干矩阵T 进行处理。该方法能够保持极化信息,有效地抑制相干斑,同时能够更好地保持点目标、纹理结构等,在处理大幅面的极化SAR数据时简单、快速、有效。      

极化SAR相干斑抑制极化白化滤波器

相干斑抑制是合成孔径雷达(SAR)图像和极化SAR图像后处理的首要问题。该文针对最优的极化相干斑抑制滤波器极化白化滤波器(PWF)仅输出一个强度图像的缺陷,对 PWF进行了改进,得到了各个极化通道的强度图像。     

Principal components transformation of multifrequency polarimetricSAR imagery

A generalized principal components transform (PCT) that maximizes the signal-to-noise ratio (SNR) and that tailors to the multiplicative speckle noise characteristics of polarimetric SAR images is developed. An implementation procedure that accurately estimates the signal and the noise covariance matrices is established. The properties of the eigenvalues and eigenvectors are investigated, revealing that the eigenvectors are not orthogonal, but the principal component images are statistically uncorrelated. Both amplitude (or intensity) and phase difference images are included for the PCT computation. The NASA/JPL polarimetric SAR imagery of P, L, and C bands and quadpolarizations is used for illustration. The capabilities of this principal components transformation in information compression and speckle reduction makes automated image segmentation and better human interpretation possible