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Shallow sea topography detection using fully Polarimetric Gaofen-3 SAR data based on swell patterns
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作者 Longyu Huang Chenqing Fan +2 位作者 Junmin Meng Jungang Yang Jie Zhang 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2023年第2期150-162,共13页
Compared to single-polarization synthetic aperture radar(SAR)data,fully polarimetric SAR data can provide more detailed information of the sea surface,which is important for applications such as shallow sea topography... Compared to single-polarization synthetic aperture radar(SAR)data,fully polarimetric SAR data can provide more detailed information of the sea surface,which is important for applications such as shallow sea topography detection.The Gaofen-3 satellite provides abundant polarimetric SAR data for ocean research.In this paper,a shallow sea topography detection method was proposed based on fully polarimetric Gaofen-3 SAR data.This method considers swell patterns and only requires SAR data and little prior knowledge of the water depth to detect shallow sea topography.Wave tracking was performed based on preprocessed fully polarimetric SAR data,and the water depth was then calculated considering the wave parameters and the linear dispersion relationships.In this paper,four study areas were selected for experiments,and the experimental results indicated that the polarimetric scattering parameterαhad higher detection accuracy than quad-polarization images.The mean relative errors were 14.52%,10.30%,12.56%,and 12.90%,respectively,in the four study areas.In addition,this paper also analyzed the detection ability of this model for different topographies,and the experiments revealed that the topography could be well recognized when the topography gradient is small,the topography gradient direction is close to the wave propagation direction,and the isobath line is regular. 展开更多
关键词 fully polarimetric sar shallow sea topography Gaofen-3 swell patterns
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An approach to estimate tree height using PolInSAR data constructed by the Sentinel-1 dual-pol SAR data and RVoG model
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作者 Yin Zhang Ding-Feng Duan 《Journal of Electronic Science and Technology》 EI CAS CSCD 2024年第3期69-79,共11页
We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Se... We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season. 展开更多
关键词 Constructed polarimetric sar data Dual polarization Sentinel-1 sar data polarimetric interferometric sar Random volume over the ground model Tree height estimation
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Information compression and speckle reduction for multifrequency polarimetric SAR images based on kernel PCA 被引量:4
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作者 Li Ying Lei Xiaogang Bai Bendu Zhang Yanning 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2008年第3期493-498,共6页
Multifrequency polarimetric SAR imagery provides a very convenient approach for signal processing and acquisition of radar image. However, the amount of information is scattered in several images, and redundancies exi... Multifrequency polarimetric SAR imagery provides a very convenient approach for signal processing and acquisition of radar image. However, the amount of information is scattered in several images, and redundancies exist between different bands and polarizations. Similar to signal-polarimetric SAR image, multifrequency polarimetric SAR image is corrupted with speckle noise at the same time. A method of information compression and speckle reduction for multifrequency polarimetric SAR imagery is presented based on kernel principal component analysis (KPCA). KPCA is a nonlinear generalization of the linear principal component analysis using the kernel trick. The NASA/JPL polarimetric SAR imagery of P, L, and C bands quadpolarizations is used for illustration. The experimental results show that KPCA has better capability in information compression and speckle reduction as compared with linear PCA. 展开更多
关键词 kernel PCA multifrequency polarimetric sar imagery information compression despeckling.
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Targets detecting in the ocean using the cross-polarized channels of fully polarimetric SAR data 被引量:3
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作者 WANG Yunhua LIU Xiaoyan +1 位作者 LI Huimin ZHANG Yanmin 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2015年第1期85-93,共9页
Azimuth ambiguities (ghost targets) discrimination is of great interest with the development of a synthet- ic aperture radar (SAR). And the azimuth ambiguities are often mistaken as actual targets and cause false ... Azimuth ambiguities (ghost targets) discrimination is of great interest with the development of a synthet- ic aperture radar (SAR). And the azimuth ambiguities are often mistaken as actual targets and cause false alarms. For actual targets, HV channel signals acquired by a fully polarimetric SAR are approximately equal to a VH channel in magnitude and phase, i.e., the reciprocity theorem applies, but shifted in phase about ±π for the first-order azimuth ambiguities. Exploiting this physical behavior, the real part of the product of the two cross-polarized channels, i.e. (SHVSVH), hereafter called A12r, is employed as a new parameter for a target detection at sea. Compared with other parameters, the contrast of A12r image between a target and the surrounding sea surface will be obviously increased when A12r image is processed by mean filtering algo- rithm. Here, in order to detect target with constant false-alarm rates (CFARs), an analytical expression for the probability density function (pdf) ofA12r is derived based on the complexWishart-distribution. Because a value of A12r is greater/less than 0 for real target/its azimuth ambiguities, the first-order azimuth ambiguities can be completely removed by this A12r-based CFAR technology. Experiments accomplished over C-band RADARSAT-2 fully polarimetric imageries confirm the validity. 展开更多
关键词 azimuth ambiguities polarimetric sar CFAR detection algorithm
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STUDY ON SPECKLE REDUCTION IN MULTI-LOOK POLARIMETRIC SAR IMAGE 被引量:1
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作者 Liu Guoqing Huang Shunji Xiong Hong A. Torre F. Rubertone(College of Electron. Eng., Univ. of Electron. Sci. & Tech. of China, Chengdu 610054)(Dept. of Remote Sensing, Alenia Spazio SPA, Rome 00131, Italy) 《Journal of Electronics(China)》 1999年第1期25-31,共7页
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 polarimet... 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. 展开更多
关键词 polarimetric sar Multi-look PROCESSING SPECKLE REDUCTION TEXTURE Classification
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CLASSIFICATION OF MULTI-LOOK POLARIMETRIC SAR IMAGERY AND POLARIZATION CHANNEL OPTIMIZATION 被引量:1
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作者 Liu Guoqing Xiong Hong Huang Shunji A. Torre F. Rubertone(College of Electron. Eng., Univ. of Electron. Sci. & Tech. of China, Chengdu 610054) (Dept. of Remote Sensing, Alenia Spazio SPA, Rome 00131, Italy) 《Journal of Electronics(China)》 1998年第4期320-325,共6页
In this paper, a new maximum likelihood (ML) classification algorithm is proposed to classify the multi-look polarimetric synthetic aperture radar (SAR) imagery. Experimental results with the NASA/JPL airborne L-band ... In this paper, a new maximum likelihood (ML) classification algorithm is proposed to classify the multi-look polarimetric synthetic aperture radar (SAR) imagery. Experimental results with the NASA/JPL airborne L-band polarimetric SAR data demonstrate the effectiveness of the new algorithm. Furthermore, when using the algorithm in the classifications with subsets of the multi-look polarimetric SAR data, the polarization-channel optimization for the terrain type classification is implemented. 展开更多
关键词 polarimetric sar Multi-look processing SPECKLE CLASSIFICATION polarization-channel OPTIMIZATION
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基于DRCNN的PolSAR图像分类综合实验设计
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作者 石俊飞 姬珊珊 +2 位作者 金海燕 聂萌萌 王伟 《实验技术与管理》 CAS 北大核心 2023年第12期74-81,130,共9页
为了让学生更好地了解和掌握深度学习TensorFlow框架和CNN网络,采用基于不同区域的多尺度卷积神经网络(DRCNN)设计了PolSAR图像分类综合设计实验,旨在实现遥感图像的自动化分类和理解。极化合成孔径雷达(polarimetric synthetic apertur... 为了让学生更好地了解和掌握深度学习TensorFlow框架和CNN网络,采用基于不同区域的多尺度卷积神经网络(DRCNN)设计了PolSAR图像分类综合设计实验,旨在实现遥感图像的自动化分类和理解。极化合成孔径雷达(polarimetric synthetic aperture radar,PolSAR)图像能够提供更加丰富的极化信息,更好地刻画地物特征,对国防建设和国家发展具有重要意义。实验利用Python语言,在CNN基础上进行改进研究,设计了多区域的多尺度CNN模型,实现了极化SAR图像的数据处理、特征学习和分类一体化设计。该实验不仅可以帮助学生综合应用图像处理与深度学习知识,理解和利用CNN来进行极化SAR图像分类的基本原理和方法,还能使学生更加深入、熟练地掌握TensorFlow框架,提高学生的科研素质和动手实践能力。 展开更多
关键词 综合实验 极化合成孔径雷达图像分类 TensorFlow框架 多尺度卷积神经网络
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Analysis of impacting factors on polarimetric SAR oil spill detection 被引量:2
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作者 SONG Shasha ZHAO Chaofang +2 位作者 AN Wei LI Xiaofeng WANG Chen 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2018年第11期77-87,共11页
Polarimetric synthetic aperture radar (SAR) oil spill detection parameters conformity coefficient (μ), Muller matrix parameters (|C|,B0 ), the eigenvalues of simplified coherency matrix (λnos) and the infl... Polarimetric synthetic aperture radar (SAR) oil spill detection parameters conformity coefficient (μ), Muller matrix parameters (|C|,B0 ), the eigenvalues of simplified coherency matrix (λnos) and the influence of SAR observing parameters, ocean environment and noise level are investigated. Radarsat-2 data are used to make systematic analysis of polarimetric parameters for different incidences, wind speeds, noise levels and the ocean phenomena (oil slick and look likes). The influence of the SAR observing parameters, the ocean environment and the noise level on the typical polarimetric SAR parameter conformity coefficient has been analyzed. The results indicate that conformity coefficient cannot be simply used for oil spill detection, which represents the image signal to the noise level to some extent. When the signals are below the noise level for the oil slick and the look likes, the conformity coefficients are negative; while the signals above the noise level corresponds to positive conformity coefficients. For dark patches (low wind and biogenic slick) with the signal below the noise, polarization features such as conformity coefficient cannot separate them with oil slick. For the signal above the noise, the oil slick, the look likes (low wind and biogenic slick) and clean sea all have positive conformity coefficients, among which, the oil slick has the smallest conformity coefficient, the look likes the second, and the clean sea the largest value. For polarimetric SAR data oil spill detection, the noise plays a significant role. So the polafimetric SAR data oil spill detection should be carried out on the basis of noise consideration. 展开更多
关键词 multi-polarimetric sar oil spill conformity coefficient noise
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AN UNSUPERVISED CLASSIFICATION FOR FULLY POLARIMETRIC SAR DATA USING SPAN/H/α IHSL TRANSFORM AND THE FCM ALGORITHM 被引量:1
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作者 Wu Yirong Cao Fang Hong Wen 《Journal of Electronics(China)》 2007年第2期145-149,共5页
In this paper, the IHSL transform and the Fuzzy C-Means (FCM) segmentation algorithm are combined together to perform the unsupervised classification for fully polarimetric Synthetic Ap-erture Rader (SAR) data. We app... In this paper, the IHSL transform and the Fuzzy C-Means (FCM) segmentation algorithm are combined together to perform the unsupervised classification for fully polarimetric Synthetic Ap-erture Rader (SAR) data. We apply the IHSL colour transform to H/α/SPANspace to obtain a new space (RGB colour space) which has a uniform distinguishability among inner parameters and contains the whole polarimetric information in H/α/SPAN.Then the FCM algorithm is applied to this RGB space to finish the classification procedure. The main advantages of this method are that the parameters in the color space have similar interclass distinguishability, thus it can achieve a high performance in the pixel based segmentation algorithm, and since we can treat the parameters in the same way, the segmentation procedure can be simplified. The experiments show that it can provide an improved classification result compared with the method which uses the H/α/SPANspace di-rectly during the segmentation procedure. 展开更多
关键词 IHSL transform Fuzzy C-Means (FCM) segmentation Fully polarimetric SyntheticAperture Rader sar) data Unsupervised classification
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Integration of SAR Polarimetric Features and Multi-spectral Data for Object-Based Land Cover Classification 被引量:7
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作者 Yi ZHAO Mi JIANG Zhangfeng MA 《Journal of Geodesy and Geoinformation Science》 2019年第4期64-72,共9页
An object-based approach is proposed for land cover classification using optimal polarimetric parameters.The ability to identify targets is effectively enhanced by the integration of SAR and optical images.The innovat... An object-based approach is proposed for land cover classification using optimal polarimetric parameters.The ability to identify targets is effectively enhanced by the integration of SAR and optical images.The innovation of the presented method can be summarized in the following two main points:①estimating polarimetric parameters(H-A-Alpha decomposition)through the optical image as a driver;②a multi-resolution segmentation based on the optical image only is deployed to refine classification results.The proposed method is verified by using Sentinel-1/2 datasets over the Bakersfield area,California.The results are compared against those from pixel-based SVM classification using the ground truth from the National Land Cover Database(NLCD).A detailed accuracy assessment complied with seven classes shows that the proposed method outperforms the conventional approach by around 10%,with an overall accuracy of 92.6%over regions with rich texture. 展开更多
关键词 synthetic aperture radar(sar) polarimetric MULTISPECTRAL data fusion object-based land cover classification
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Structural adaptive and optimal speckle filtering in multilook full polarimetric SAR images
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作者 Sun Nan Zhang Bingchen Wang Yanfei 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第2期217-222,共6页
A novel approach is proposed for speckle reduction in multilook full polarimetric SAR images. In contrast to others, this approach adopts an enhanced structure detection method to estimate the parameters of the polari... A novel approach is proposed for speckle reduction in multilook full polarimetric SAR images. In contrast to others, this approach adopts an enhanced structure detection method to estimate the parameters of the polarimetric covariance matrix for the multilook polarimetric whitening filtering (MPWF) algorithm and thus a structural adaptive and optimal speckle filter is developed. To evaluate the present approach, NASA SIR-C/X- SAR, L band, four-look processed polarimetric SAR data of the Tian-Mountain Forest is used for simulation. Experimental results demonstrate the effectiveness of this novel filtering algorithm in case of both speckle reduction and preservation of texture information. Comparisons with other methods are also made. 展开更多
关键词 MPWF Geometrical-ratio detectors ESDMPWF SPECKLE Multilook polarimetric sar.
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STATISTICAL ANALYSIS OF MULTI-LOOK POLARIMETRIC SAR IMAGERY
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作者 A.Torre F.Rubertone 《Journal of Electronics(China)》 1999年第2期172-178,共7页
With a multiplicative speckle model, this paper shows the multi-look polarimetric synthetic aperture radar (SAR) data obeys a generalized K-distribution. To validate this distribution model, the multi-look intensity K... With a multiplicative speckle model, this paper shows the multi-look polarimetric synthetic aperture radar (SAR) data obeys a generalized K-distribution. To validate this distribution model, the multi-look intensity K-distribution is particularly tested. The relationship between the heterogeneity coefficient of the scene and the proper statistical model is experimentally established. In addition, based on the results of the statistical analysis, an adaptive classification scheme is presented, and the improved classification shows the importance of the statistical analysis. 展开更多
关键词 polarimetric sar Multi-look PROCESSING SPECKLE STATISTICAL analysis CLASSIFICATION
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Supervised polarimetric SAR classification method based on Fisher linear discriminant
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作者 王鹏 李洋 洪文 《Journal of Beijing Institute of Technology》 EI CAS 2012年第2期264-268,共5页
A supervised polarimetric SAR land cover classification method was proposed based on the Fisher linear discriminant. The feature parameters used in this classification method could be se- lected flexibly according to ... A supervised polarimetric SAR land cover classification method was proposed based on the Fisher linear discriminant. The feature parameters used in this classification method could be se- lected flexibly according to land covers to be classified. Polarimetric and texture feature parameters extracted from co-registered multifrequency and multi-temporal polarimetric SAR data could be com- bined together for classification use, without consideration of the dimension difference of each fea- ture parameter and the joint probability density function of those parameters. Experimental result with AGRSAR L/C-band full polarimetric SAR data showed that a total classification accuracy of 94. 33% was achieved by combining the polarimetric with texture feature parameters extracted from L/C dual band SAR data, demonstrating the effectiveness of this method. 展开更多
关键词 polarimetric sar land cover classification supervised classification Fisher linear dis-criminant
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A method for coastal oil tank detection in polarimetric SAR images based on recognition of T-shaped harbor
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作者 LIU Chun XIE Chunhua +2 位作者 YANG Jian XIAO Yingying BAO Junliang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2018年第3期499-509,共11页
To automatically detect oil tanks in polarimetric synthetic aperture radar(SAR) images, a coastal oil tank detection method is proposed based on recognition of T-shaped harbor. First of all, the T-shaped harbor is d... To automatically detect oil tanks in polarimetric synthetic aperture radar(SAR) images, a coastal oil tank detection method is proposed based on recognition of T-shaped harbor. First of all, the T-shaped harbor is detected to locate the region of interest(ROI) of oil tanks. Then all suspicious targets in the ROI are extracted by the segmentation of strong scattering targets and the classifier of H/α. The template targets are selected from the suspicious targets by the combination of a proposed circular degree parameter and the similarity parameter(SP) of the polarimetric coherency matrix. Finally, oil tanks are detected according to the statistics of the similarity parameter between each suspicious target and template targets in ROI. Polarimetric SAR data acquired by RADARSAT-2 over Berkeley and Singapore areas are used for testing. Experiment results show that most of the targets are correctly detected and the overall detection rate is close to 80%.The false rate is effectively reduced by the proposed algorithm compared with the method without T-shaped harbor recognition. 展开更多
关键词 oil tank detection T-shaped harbor recognition polarimetric synthetic aperture radar(sar)
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ADAPTIVE MODEL-BASED SCATTERING DECOMPOSITION OF POLARIMETRIC SAR INTERFEROMETRY
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作者 Xu Liying Li Shiqiang +1 位作者 Deng Yunkai Robert Wang 《Journal of Electronics(China)》 2013年第5期463-468,共6页
In this paper,a new decomposition method is proposed to solve the problems that vegetation component is overestimated and is not sensitive to directional scattering features with traditional polarimetric Synthetic Ape... In this paper,a new decomposition method is proposed to solve the problems that vegetation component is overestimated and is not sensitive to directional scattering features with traditional polarimetric Synthetic Aperture Radar(SAR)decomposition.It uses a Polarimetric Interferometric Similarity Parameter(PISP)calculated from Polarimetric SAR Interferometry(PolInSAR)datasets to the scattering decomposition.The PISP is proposed to reveal the geometric sensitivity of SAR interferometry.It is defined by three optimized mechanisms obtained from PolInSAR datasets,therefore,it not only relates to the coherent scattering mechanism closely,but also sufficiently uses the phase and amplitude information.The PISP of building is high,and forest’s PISP is low.The proposed method uses the PISP as a judge condition to select different vegetation model adaptively.The decomposition results show the proposed method can effectively solve the vegetation ingredients overestimation problem.In addition,it is sensitive to the directional scattering. 展开更多
关键词 Synthetic Aperture Radar(sar) polarimetric sar Interferometry(polInsar) Scattering decomposition
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Analysis of a Residual Model for the Decomposition of Polarimetric SAR Data
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作者 Xiaojing Bai Binbin He Xiaowen Li 《Advances in Remote Sensing》 2013年第2期120-126,共7页
Accurate estimation of the double-bounce scattering fd and surface scattering fs coefficients with Freeman-Durden decomposition is still difficult. This difficulty arises because overestimation of the volume scatterin... Accurate estimation of the double-bounce scattering fd and surface scattering fs coefficients with Freeman-Durden decomposition is still difficult. This difficulty arises because overestimation of the volume scattering energy contribution Pv leads to negative values for fd and fs. A generalized residual model is introduced to estimate fd and fs. The relationship between Pv and the residual model is analyzed. Eigenvalues computed from the residual model must be positive to explain physical scattering mechanisms. The authors employ a new volumetric scattering model to minimize Pv as calculated by several decomposition methods. It is concluded that decreasing Pv can help reduce negative energy. This conclusion is validated using actual polarimetric SAR data. 展开更多
关键词 Freeman-Durden DECOMPOSITION polarimetric sar RESIDUAL Model NEGATIVE SCATTERING ENERGY
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基于融合距离的极化SAR图像非局部均值滤波
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作者 曾顶 殷君君 杨健 《系统工程与电子技术》 EI CSCD 北大核心 2024年第5期1493-1502,共10页
在极化合成孔径雷达(synthetic aperture radar,SAR)图像降噪领域,常见的非局部均值滤波仅依靠像素间的统计距离进行相似性度量,忽略了像素点的空间信息。本文结合极化SAR数据统计特性和图像空间特征作为像素间的相似性度量,提出了一种... 在极化合成孔径雷达(synthetic aperture radar,SAR)图像降噪领域,常见的非局部均值滤波仅依靠像素间的统计距离进行相似性度量,忽略了像素点的空间信息。本文结合极化SAR数据统计特性和图像空间特征作为像素间的相似性度量,提出了一种利用融合距离来计算相邻窗口权重的方法——基于融合距离的非局部均值滤波器。融合距离的引入使得滤波器能够更全面的评估像素间的相似性,从而得到更合适的像素权重。此外,本方法还引进变异系数对邻域窗口的权重进行评估,通过该参数可以控制滤波的程度。在多幅极化SAR图像上的实验结果表明,所提出的滤波器能够在有效抑制斑点噪声的同时保留较为完整的图像边缘信息和极化散射特性。 展开更多
关键词 极化合成孔径雷达 非局部均值滤波 相似性度量 变异系数
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微波视觉三维SAR实验系统及其全极化数据处理方法
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作者 仇晓兰 罗一通 +7 位作者 宋舒洁 彭凌霄 程遥 颜千程 上官松涛 焦泽坤 张柘 丁赤飚 《雷达学报(中英文)》 EI CSCD 北大核心 2024年第5期941-954,共14页
三维合成孔径雷达在测绘制图、防灾减灾等诸多领域有应用潜力,已经成为SAR的重要研究方向。为减少三维SAR的观测次数或天线阵元数量,推动三维SAR的应用和发展,中国科学院空天信息创新研究院牵头研制了微波视觉三维SAR实验系统,旨在为微... 三维合成孔径雷达在测绘制图、防灾减灾等诸多领域有应用潜力,已经成为SAR的重要研究方向。为减少三维SAR的观测次数或天线阵元数量,推动三维SAR的应用和发展,中国科学院空天信息创新研究院牵头研制了微波视觉三维SAR实验系统,旨在为微波视觉SAR三维成像提供实验平台和数据。该文针对微波视觉三维SAR实验系统及其全极化数据处理方法进行介绍,涵盖了极化校正、极化相干增强、极化约束三维成像、三维融合可视化等全流程的关键步骤。基于发布的SAR微波视觉三维成像全极化数据集,给出了三维成像结果示例,验证了微波视觉三维SAR实验系统的全极化性能以及处理方法的有效性。该文发布的数据集将为SAR三维成像研究提供良好的数据条件。 展开更多
关键词 sar三维成像 微波视觉 极化阵列干涉sar 无人机载sar 多角度
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基于双极化SAR数据的深圳市地表形变研究
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作者 刘五杰 田婕 袁方 《城市勘测》 2024年第5期137-142,共6页
旨在挖掘数据的极化信息,利用覆盖深圳市填海地区的Sentinel-1A卫星IW模式升轨影像,进行基于双极化SAR数据提取地表形变的相对优化极化组合选择实验,以PSInSAR技术处理影像,获取填海区域地表形变速率,分析重点沉降区域时序形变特征,结合... 旨在挖掘数据的极化信息,利用覆盖深圳市填海地区的Sentinel-1A卫星IW模式升轨影像,进行基于双极化SAR数据提取地表形变的相对优化极化组合选择实验,以PSInSAR技术处理影像,获取填海区域地表形变速率,分析重点沉降区域时序形变特征,结合SBAS技术处理结果进行对比验证。实验表明,使用VV+VH极化组合方式的SAR数据在地表形变提取的精度与范围上均优于VV极化方式的SAR数据;发现研究区域主要有三个形变漏斗,分布在宝安区福州大道附近、蛇口水湾路附近、福田区益田地铁站附近。最大沉降速率-16.7~-14.26 mm/a,集中在福田区南部;最大抬升速率为7.6~10.4 mm/a,集中在蛇口区域。 展开更多
关键词 PSINsar 极化sar 填海区 地表形变
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Fine classification of rice paddy using multitemporal compact polarimetric SAR C band data based on machine learning methods
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作者 Xianyu GUO Junjun YIN +3 位作者 Kun LI Jian YANG Huimin ZOU Fukun YANG 《Frontiers of Earth Science》 SCIE CSCD 2024年第1期30-43,共14页
Rice is an important food crop for human beings.Accurately distinguishing different varieties and sowing methods of rice on a large scale can provide more accurate information for rice growth monitoring,yield estimati... Rice is an important food crop for human beings.Accurately distinguishing different varieties and sowing methods of rice on a large scale can provide more accurate information for rice growth monitoring,yield estimation,and phenological monitoring,which has significance for the development of modern agriculture.Compact polarimetric(CP)synthetic aperture radar(SAR)provides multichannel information and shows great potential for rice monitoring and mapping.Currently,the use of machine learning methods to build classification models is a controversial topic.In this paper,the advantages of CP SAR data,the powerful learning ability of machine learning,and the important factors of the rice growth cycle were taken into account to achieve high-precision and fine classification of rice paddies.First,CP SAR data were simulated by using the seven temporal RADARSAT-2 C-band data sets.Second,20-two CP SAR parameters were extracted from each of the seven temporal CP SAR data sets.In addition,we fully considered the change degree of CP SAR parameters on a time scale(ΔCP_(DoY)).Six machine learning methods were employed to carry out the fine classification of rice paddies.The results show that the classification methods of machine learning based on multitemporal CP SAR data can obtain better results in the fine classification of rice paddies by considering the parameters ofΔCP_(DoY).The overall accuracy is greater than 95.05%,and the Kappa coefficient is greater than 0.937.Among them,the random forest(RF)and support vector machine(SVM)achieve the best results,with an overall accuracy reaching 97.32%and 97.37%,respectively,and Kappa coefficient values reaching 0.965 and 0.966,respectively.For the two types of rice paddies,the average accuracy of the transplant hybrid(T-H)rice paddy is greater than 90.64%,and the highest accuracy is 95.95%.The average accuracy of direct-sown japonica(D-J)rice paddy is greater than 92.57%,and the highest accuracy is 96.13%. 展开更多
关键词 compact polarimetric(CP)sar rice paddy machine learning fine classification MULTITEMPORAL
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