An improved building detection approach using L-band POLSAR two-dimensional time-frequency decomposition over oriented built-up areas     

Lei Deng  Ying He  Zhi-hui Mao  Jie Yu 《地理信息系统科学与遥感》2019,56(1):1-21

The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value.  相似文献   

SAR image despeckling with a multilayer perceptron neural network     

Xiao Tang  Lei Zhang  Xiaoli Ding 《International Journal of Digital Earth》2019,12(3):354-374

Speckle noise in synthetic-aperture radar (SAR) images severely hinders remote sensing applications; therefore, the appropriate removal of speckle noise is crucial. This paper elaborates on the multilayer perceptron (MLP) neural-network model for SAR image despeckling by using a time series of SAR images. Unlike other filtering methods that use only a single radar intensity image to derive their parameters and filter that single image, this method can be trained using archived images over an area of interest to self-learn the intensity characteristics of image patches and then adaptively determine the weights and thresholds by using a neural network for image despeckling. Several hidden layers are designed for feedforward network training, and back-propagation stochastic gradient descent is adopted to reduce the error between the target output and neural-network output. The parameters in the network are automatically updated in the training process. The greatest advantage of MLP is that once the despeckling parameters are determined, they can be used to process not only new images in the same area but also images in completely different locations. Tests with images from TerraSAR-X in selected areas indicated that MLP shows satisfactory performance with respect to noise reduction and edge preservation. The overall image quality obtained using MLP was markedly higher than that obtained using numerous other filters. In comparison with other recently developed filters, this method yields a slightly higher image quality, and it demonstrates the powerful capabilities of computer learning using SAR images, which indicate the promising prospect of applying MLP to SAR image despeckling.  相似文献   

合成孔径雷达差分干涉测量（D-InSAR）技术在多年冻土区地表变形监测中的应用   总被引：2，自引：2，他引：0  

赵韬  张明义  裴万胜  王金国  岳攀  毕骏 《冰川冻土》2020,42(3):1087-1097

多年冻土区地表变形严重影响着区域内生态环境和工程设施的稳定性。合成孔径雷达差分干涉测量（differential interferometric synthetic aperture radar， D-InSAR）技术作为一种新型的空间对地观测技术， 为多年冻土区地表变形监测提供了新方法。通过近20年的不断深入研究， 利用D-InSAR技术的多年冻土区地表变形监测取得了大量研究成果。首先介绍了D-InSAR技术测量地表变形的理论基础， 进而概述了D-InSAR技术在多年冻土区地表变形测量中的应用现状， 然后总结了D-InSAR测量过程中存在的关键问题及可能的解决方法。在此认识和分析的基础上， 对D-InSAR技术今后在多年冻土区地表变形监测中的发展方向进行了探讨， 以期为D-InSAR技术在多年冻土区地表变形监测中的推广应用和深入研究提供参考。  相似文献   

结构增强型生成对抗网络SAR图像超分辨率重建     

闵锐  杨学志  董张玉  陈鲸 《地理与地理信息科学》2021,37(2):47-53

针对利用生成对抗网络模型(Generative Adversarial Network,GAN)重建SAR(Synthetic Aperture Radar)图像存在边缘细节信息不足和“伪影”(artifacts)现象,该文基于增强型超分辨率生成对抗网络(Enhanced Super-Resolution Generative Adversarial Networks,ESRGAN)光学模型,重新设计生成网络上采样重建模块和结构损失函数,提出一种结构增强型生成对抗网络SAR图像超分辨率重建算法,包括特征提取、特征增强和上采样重建3个模块:在特征提取模块采用小尺度卷积层对输入SAR图像进行低层次特征提取;在特征增强模块采用多个级联残差密集块(Residual-in-Residual Dense Block,RRDB)和卷积层提取输入特征;在上采样重建模块交替使用最近邻插值(Nearest Neighbor Interpolation,NNI)和亚像素卷积(Sub-Pixel Convolution,SPC)对特征进行放大重建,使特征信息交互融合。与传统插值算法和经典深度学习重建算法相比,该算法在视觉效果和定量评价方面均有显著提升,能够在保持原网络模型重建图像内容信息不丢失的基础上,增强重建图像边缘细节信息和减缓“伪影”现象,有利于后续目标识别和灾害监测等工作开展。  相似文献   

基于双分支卷积神经网络的SAR与多光谱图像融合实验     

吴佼华  杨学志  方帅  董张玉 《地理与地理信息科学》2021,37(2):22-30

针对合成孔径雷达(Synthetic Aperture Radar,SAR)和多光谱(Multi-Spectral,MS)融合图像中存在的空间细节模糊和颜色失真问题,该文兼顾光谱监督和空间细节监督,设计光谱损失函数和空间细节损失函数,提出一种基于双分支卷积神经网络(Convolution Neural Network,CNN)的SAR和MS图像融合算法。该算法网络框架包含光谱保持和细节提升两个分支:光谱保持分支通过上采样MS图像连接到网络的输出,直接将光谱信息传递到融合图像中;细节提升分支对SAR和MS图像通过高通滤波提取高频细节信息,然后应用CNN对细节信息进行特征提取、特征融合及重建,最后将重建的细节信息叠加到上采样的MS图像,得到融合结果。以哨兵-1B GRD级别的SAR图像和Landsat8卫星多光谱图像为实验数据,通过与传统融合算法和深度学习算法RSIFNN进行对比,结果表明,该文算法在定性和定量评价方面效果更好,能够在保持光谱信息的基础上增强多光谱图像的空间细节信息,有利于后续地物分类和目标识别等工作的开展。  相似文献   

基于DInSAR的洪河国家级自然保护区沼泽水位相对变化量监测研究     

付波霖  蓝斐芜  邓腾芳  李颖  何宏昌  范冬林  高二涛  杨高 《湿地科学》2021,(1)

水文是沼泽形成、发育和演化的决定性因素。目前,沼泽水位的监测仍然以实地观测为主,需要花费大量的人力和物力。以洪河国家级自然保护区为研究区,利用2007年6~10月星载相控阵L波段合成孔径雷达(phase array type L-band synthetic aperture radar,L-band PALSAR)数据和2015年6~11月C波段Sentinel-1A合成孔径雷达(synthetic aperture radar,SAR)数据,采用合成孔径雷达差分干涉测量(differential interferometric synthetic aperture radar,DInSAR)技术,提取出研究区沼泽的地表形变相位,计算出研究区沼泽水位相对变化量,构建了研究区沼泽水位相对变化量遥感监测经验估算公式,实现了对研究区沼泽年内水位变化量的遥感监测,研究了不同时相浅水沼泽区和深水沼泽区干涉相干性的差异;采用方差分析和回归分析方法,在水位观测站、浅水沼泽区和深水沼泽区3种尺度上,分别对利用两种数据计算出的沼泽水位相对变化量,进行了精度验证和显著性检验。研究结果表明,植物生长期和植物空间格局都对沼泽干涉相干性产生影响,8~10月研究区干涉相干性要好于6~7月,浅水沼泽区干涉相干性要高于深水沼泽区,前者的干涉相干系数比后者的大10%~35%;计算出的沼泽水位相对变化量与地面实测的水位变化量的变化趋势吻合度较高,2007年6~7月和9~10月浅水沼泽区的水位波动幅度较大,水位变化量超过了0.70 m。  相似文献   

Yamaguchi分解Notch滤波的全极化SAR图像舰船目标检测     

刘伟  陈建宏  甄勇  赵拥军 《测绘科学技术学报》2017,34(1)

极化合成孔径雷达数据蕴含了丰富的地物极化散射信息,已广泛应用于海上舰船目标检测研究。针对极化相干矩阵无法直接用于分析特定散射体物理特性的缺陷,利用Yamaguchi极化分解改进了极化Notch滤波器。将基于模型的极化分解方法引入Notch滤波器,利用表面散射、二次散射、体散射和螺旋体散射等散射机制的能量构造散射矢量代替极化相干散射矢量,并加入功率能量因子,构造新的极化SAR图像Notch滤波器。Radarsat-2全极化SAR图像实验结果表明,改进算法有效增强了舰船目标与海杂波背景间的对比度,检测性能优越。  相似文献   

利用小基线集技术(SBAS)监测泉州地区地表形变     

陈志谋  陈金座  罗楚楚  姚俊启  陈进清  崔家武 《测绘工程》2017,26(7)

差分干涉测量(DInSAR)技术可用于监测厘米级甚至毫米级的地表形变。文中选用2007—2011年期间19景日本ALOS1/PALSAR数据,采用短基线集技术(SBAS)获取了该地区的形变时间序列和平均沉降速率。研究结果表明:泉州东南部地区整体上呈抬升态势,上升速率为5mm/a左右,主要是受到亚欧板块和西太平洋板块互相挤压作用的结果;泉州东南部有多处出现地表沉降,沉降的结果与泉州市统计的地区地下水开采数据相当吻合,因此沉降主要与地下水过度开采相关。  相似文献   

全极化SAR图像中溢油极化特征研究   总被引：2，自引：1，他引：1  

郑洪磊  张彦敏  王运华  张晰  孟俊敏 《海洋学报(英文版)》2017,36(5):105-114

相比于单极化SAR图像,全极化SAR图像不仅能体现海面目标的几何特征、后向散射特征,还能体现目标的极化特征。因此,在溢油检测方面,极化SAR更具优势。特征提取作为溢油检测的关键步骤,直接影响到溢油检测的精度。在本文中,我们分析了全极化SAR图像中海面溢油的极化特征,如极化散射熵、平均散射角等。并提出了新的极化特征P,该特征参数能够反映海面目标电磁散射过程中布拉格散射机制和镜面散射机制的比例。为了研究极化特征溢油检测的能力,本文基于SIR-C/X-SAR和Radarsat-2全极化SAR图像开展了相关实验,并对比分析了溢油的多种极化特征。实验结果显示,在中低风速情况下,C波段溢油探测效果优于L波段;本文提出的极化特征P对海面散射机制敏感;基准高度和特征参数P在C波段比其他极化特征更适于溢油检测。  相似文献   

背景场对变分方法海面风速反演结果的影响          下载免费PDF全文

姜祝辉  陈建  沈晓晶 《应用海洋学学报》2022,41(1):130-135

利用前期提出的合成孔径雷达反演海面风场变分方法新解法,开展背景场对合成孔径雷达反演海面风场变分方法风速反演结果影响的模拟试验分析.模拟试验表明,变分方法有效解决了直接反演方法的两大缺陷:一是当背景场风速较大的时候,合成孔径雷达后向散射系数对风速不敏感,直接导致较大的风速反演误差;二是当背景场风向存在误差时,将导致后向散...  相似文献