Feature preserving speckle filtering of the SAR images by wavelet transform

Synthetic Aperture Radar (SAR) images are corrupted by speckle noise due to random interference of electromagnetic waves. The speckle degrades the quality of the image and makes it difficult to interpret, analyse and classify. This paper proposes a method that reduces the speckle and preserves the features by using scale-space correlation between the scales. The results show that the proposed method is better than the widely used filters based on the spatial domain, such as Lee, Kuan, Frost, Ehfrost, Median, Gamma filters in terms of feature preservation. Moreover the proposed method achieves a wide range of balances between speckle reduction and feature preservation, and thus is applicable in different applications such as road detection, detection/ identification of bridge, and ribbon like structures. Furthermore, the proposed method does not require prior modeling of either the image or noise statistics. It uses the variance of the detail wavelets coefficients to estimate noise variance.     

Feature selection for airborne LiDAR data filtering: a mutual information method with Parzon window optimization

ABSTRACT

Filtering is one of the key steps for Digital Elevation Model (DEM) generation from airborne Light Detection and Ranging (LiDAR) data. Machine-learning-based filters have emerged as a class of filtering algorithms in recent years. Most existing studies mainly focus on feature generation due to limited available features a point cloud possesses. More than 30 features have been described in the existing literature. But most generated features are based on geometric information of points. Several redundant and irrelevant features may not necessarily improve the filtering accuracy. Hence, this paper proposes a feature-selection method using minimal-Redundancy-Maximal-Relevance (mRMR) combined with Parzen window optimization to deal with both discrete and continuous features. An optimal/suboptimal feature subset is constructed for machine-learning filters in various landscapes. Experimental results based on AdaBoost show that height-related features, particularly height itself, are of the greatest significance in both urban and rural scenes. Moreover, different subsets can be selected from the datasets of the two landscapes by our feature-selection strategy, which increases the data relevance for describing each geographical landscape. This study provides guidelines for the selection of optimal/suboptimal features for point cloud filtering based on machine-learning algorithms.     

基于本体属性的基础地理信息概念语义相似性计算模型

语义相似性对于知识自动共享与集成起着非常重要的作用。在许多地理信息的应用领域,通常直接将分类体系作为领域(或任务)本体,并基于此计算概念间的语义距离以实现相似度计算。该方法虽然能够快速、简便地计算概念间的语义相似度,但是有时却因为分类体系的改变而造成相同概念间的相似度产生差异,甚至可能是错误的计算结果。本文面向基础地理信息领域,利用属性枚举方法表达概念的本质语义特征,从基础地理信息概念的内涵出发,提出基于本体属性的语义相似性计算模型。该模型将每个概念表达为本体属性集合,利用相关本体属性的相似性,结合权重信息计算概念的相似性。最后从基础地理信息概念中提取出100组样本,计算概念间的语义相似度并验证基于本体属性模型的有效性。实验结果表明基于本体属性的模型能更合理地计算出基础地理信息概念的相似度。     

一种WMS领域主题文本提取及元数据扩展方法

由于网络地图服务（Web map service,WMS）元数据缺乏显式的领域主题描述机制,用户很难准确、全面地发现目标领域的地图数据资源。提出了一种面向地理信息资源检索的WMS领域主题文本提取及元数据扩展方法。首先,设计了一种非监督文本分类算法,利用地球与环境术语集语义网（semantic Web of Earth and environmental terminology,SWEET）和大型英语词汇语义网WordNet,综合计算WMS元数据能力文档中地学术语、通识型词汇与领域主题的语义相关度,为WMS及其图层提取多标签主题。然后,基于ISO19115 2003地理信息元数据标准,为WMS元数据组织模型扩展领域主题。实验结果表明,所提出的WMS元数据主题分类算法取得了较高的查准率和查全率,且相较于朴素贝叶斯、线性支持向量机（support vector machine,SVM）和逻辑回归等方法,整体上有较大的优势。该方法有望应用于当前的地理信息门户和目录服务,辅助用户快速、准确地定位目标领域的地图服务资源。     

基于小波阈值优化和边缘检测的SAR影像斑点噪声滤除

探讨在小波频域内进行SAR斑点噪声分析的特点和优势，回顾小波频域斑点噪声滤除的方法，结合前人阈值优化和边缘检测蝗思想提出一种新的斑点噪声消除方法，试验表明所研究的噪声滤除方法，同各种空间域滤波方法和已有的小波频域滤波方法比较，在噪声滤除和信息保留两方面的综合效果有明显提高，具有一定的应用价值。     

DLG数据更新中的拓扑关系自适应研究

针对异构矢量数据相互转换时地理要素间拓扑关系一致性维护的问题,本文提出了一种拓扑关系自适应更新的方法。在分析地理要素间拓扑关系的基础上,研究其空间变化引起的拓扑关系变化,并以变化后的拓扑关系合理性为判断依据,提出地理要素相应的拓扑关系自适应策略。将理论研究进行工程化应用,先将地理要素的拓扑关系自适应策略转化为可编辑的XML文档,然后采用ArcGIS Add-in方式开发插件工具,实现了更新DLG数据时地理要素间拓扑关系的自适应更新,可以减少人工操作,提高更新效率。     

Object tracking in surveillance video based on Siamese network considering geographical spatiotemporal constraints

Identifying and tracking objects in surveillance videos is an important means of mining information during surveillance. Currently, most object-tracking methods rely only on image features, which cannot accurately express the motion of the tracked object in real geographical scenes and are easily influenced by occlusion and surrounding objects having similar features. However, tracked objects, such as pedestrians and vehicles, usually move in geographical space with fixed patterns of motion, and the motion in a short time is constrained by geographical space and time, the motion trajectory is predictable, and the range of motion is limited. Therefore, based on the SiamFC object tracking framework, this study introduces geographical spatiotemporal constraints into the tracking framework and proposes the GeoSiamFC method. The objective of this is to: (1) construct the mapping relationship between geographical space and image space to solve the problem that the pixel movement within the image after perspective imaging cannot accurately express the motion of the tracked object in a real geographical scene; (2) add candidate search areas according to the predicted trajectory location to correct the tracking errors caused by the occlusion of the object; and (3) focus on the search for the range of motion of the mapped pixel within the image space according to the limited geographical range of motion of the tracked objects in a certain time to reduce the interference of similar objects within the search area. In this study, separate experiments were conducted on a common test dataset using multiple methods to deal with challenges such as occlusion and illumination changes. In addition, a robust test dataset with noise addition and luminance adjustment based on the common test dataset was used. The results show that GeoSiamFC outperforms other object-tracking methods in the common test dataset with a precision score of 0.995 and a success score of 0.756 compared with most other object-tracking algorithms under the base condition of using only shallow networks. Moreover, GeoSiamFC maintained the highest precision score (0.970) and high success score (0.734) in the more challenging robust test dataset as well. The tracking speed of 59 frames per second far exceeds the real-time requirement of 25 FPS. Geographical spatiotemporal constraints were considered to improve tracker performance while providing real-time feedback on the motion trajectory of the target in geographical space. Thus, the proposed method is suitable for real-time tracking of the motion trajectory of a target in real geographical scenes in various surveillance videos.     

对地理信息系统地理性的认识

从操作对象、数据管理、分析模型、系统功能、GIS应用等五方面对地理信息系统所具有的或所表现出的地理学特性作了初步的探讨,认为：地理学是GIS的理论依托,地理学特性、地理区域分析方法、地理思维方式渗透在GIS的整个工作流程中,成为GIS区别于其他信息系统的本质特征,而计算机等相关技术作为实现GIS功能的技术支持。不应该成为GIS的理论根本。GIS是地理科学体系的重要组成部分,是现代地理研究的重要手段和工具,具有显著的地理性,GIS专业学生应当重视地理学理论的学习。     

Unsupervised segmentation of high-resolution remote sensing images based on classical models of the visual receptive field

Here, we describe an unsupervised segmentation method incorporating log-Gabor (LG) filters and a Markov random field (MRF) model for high-resolution (HR) remote sensing (RS) images, based on classical models of the visual receptive field. LG filters were utilised to model the receptive fields of the simple cells in the primary visual cortex and extract detailed features from HR–RS images followed by construction of image pyramid through wavelet decomposition to simulate the hierarchical structure of the visual sensing system. Finally, based on the original HR–RS images, their detailed features and the image pyramid, the MRF image segmentation model was applied to obtain the final segmentation result. Real HR–RS images were used as experimental data to validate the proposed method, both qualitatively (visually) and numerically (with the overall accuracy and Kappa index).The experimental results indicate that the proposed method is effective, feasible and robust to noise.     

基于语义的地理概念范例构造方法

跨领域地理信息的语义共享的实现依赖于对地理概念的明确理解,而由于文字的模糊性,仅从地理概念的文字描述或定义来理解往往会有一定歧义。从认知原理看,地理概念的形成更多是对其外延进行归纳,并在大脑中构建出概念范例来完成。探索了一种在地理信息领域中构造地理概念范例的方法,即通过在概念文字描述中提取确定概念范畴及外延的本体属性,通过外延和实体属性来选择实例作为表达概念显著特征的范例。通过两个构建范例的案例验证了该方法的有效性。     

On the spectral consistency of the altimetric ocean and geoid surface: a one-dimensional example

Geoid models from the new generation of satellite gravity missions, such as GRACE and GOCE, in combination with sea surface from satellite altimetry allow to obtain absolute dynamic ocean topography with rather high spatial resolution and accuracy. However, this implies combination of data with fundamentally different characteristics and different spatial resolutions. Spectral consistency would imply the removal of the short-scale features of the altimetric sea surface height by filtering, to provide altimetric data consistent with the resolution of the geoid field. The goal must be to lose as little as possible from the high precision of the altimetric signal. Using a one-dimensional example we show how the spectrum is changing when a function defined only on a limited domain (ocean in the real case) is extended or not as to cover the complete domain (the whole sphere in the real case). The results depend on the spectral characteristics of the altimetric signal and of the applied filter. Referring to the periodicity condition, as it is requested in the case of Fourier analysis, the action of the two classical filters (Ideal Low Pass and Gauss filter) and of two alternative procedures (wavelets and Slepian) is studied.     

一种改进的SAR图像斑点噪声滤波方法

在过去的 2 0多年中 ,提出了许多去除SAR图像斑点噪声的方法。这些方法的主要目的是去除斑点噪声而不破坏图像的空间分辨率和边缘信息。理论和实践表明去除图像的斑点噪声和保持图像边缘信息是无法同时完成的。现有大部分滤波器是在去除噪声和保持边缘之间进行折衷。在Han等人方法的基础上提出了一种在去除噪声和保持边缘方面最优的滤波器。它在去除噪声同时能够有效保持边缘信息     

基于SPOT 5图像的岩溶地貌单元自动提取方法

通过对峰林、峰丛和岩溶洼地3者的地理特征和影像特征的研究,基于遥感图像本底值提出了能有效反映目标特征的遥感指数——植被指数、土壤亮度指数、图像主成分变换第1主成分值及地形数据等,并构建了遥感指数的集成计算法,建立了遥感自动提取模型.指数集成运算法能够有效地增大峰丛、峰林与其他地物之间的光谱差异,使这些岩溶地貌单元的灰度值高于其他地物,从而利于岩溶地貌单元提取阈值的自动选取.基于构建的遥感自动提取模型先提取了峰丛、峰林信息,并在此基础上提取了岩溶洼地信息.经实验研究表明,该方法具有较高的提取精度和效率.     

基于约束D-TIN的等高线簇与河网协同综合方法

传统制图综合中针对水系、地貌等不同地理要素的分治策略,往往导致综合后要素目标之间在空间与语义上的冲突.考虑地形与河流之间的空间依赖性,提出一种等高线簇与河网协同的制图综合方法,即利用两种要素目标顶点在约束D-TIN描述下的空间邻近关系,并通过提取和组织谷地等高线弯曲段数据,构建两要素有效协同关系.在此基础上将等高线按所...     

Filter design for GOCE gravity gradients

The GOCE satellite observes gravity gradients with unprecedented accuracy and resolution. The GOCE observations are reliable within a well-defined measurement bandwidth. In this study, different finite and infinite impulse response filters have been designed to obtain the demanded pass. Exhaustive time and frequency domain investigations prove that the proposed infinite impulse response filter can be a real competitor of the existing solution of the filtering problem.     

GeoNat v1.0: A dataset for natural feature mapping with artificial intelligence and supervised learning

Machine learning allows “the machine” to deduce the complex and sometimes unrecognized rules governing spatial systems, particularly topographic mapping, by exposing it to the end product. Often, the obstacle to this approach is the acquisition of many good and labeled training examples of the desired result. Such is the case with most types of natural features. To address such limitations, this research introduces GeoNat v1.0, a natural feature dataset, used to support artificial intelligence‐based mapping and automated detection of natural features under a supervised learning paradigm. The dataset was created by randomly selecting points from the U.S. Geological Survey’s Geographic Names Information System and includes approximately 200 examples each of 10 classes of natural features. Resulting data were tested in an object‐detection problem using a region‐based convolutional neural network. The object‐detection tests resulted in a 62% mean average precision as baseline results. Major challenges in developing training data in the geospatial domain, such as scale and geographical representativeness, are addressed in this article. We hope that the resulting dataset will be useful for a variety of applications and shed light on training data collection and labeling in the geospatial artificial intelligence domain.     

一种河口湾海岸线渐进化简方法

形态复杂的河口湾海岸线自动化简是当前线要素化简研究的难点之一。在现有研究基础上,结合地理特征影响下河口湾海岸线形态特点及海图综合约束,提出一种河口湾海岸线渐进化简方法。该方法以约束Delaunay三角网为支撑构建河口湾骨架线二叉树模型,结构化表达河口湾海岸线形态特征;基于此模型,通过叶子流路渐进取舍、"退化"充分化简细小弯曲或弯曲细小部分,通过局部夸大消除河口湾内视觉冲突等,实现河口湾海岸线化简。试验结果表明,该方法充分化简目标尺度下不可视的局部细节,顾及河口湾海岸线整体形态特征保持,在几何层次、地理层次上都具有一定优越性,适于多种形态河口湾海岸线化简应用。     

视频与GIS协同的交通违规行为分析方法

针对人工监测无法及时、高效地发现视频中车辆和行人违规情况的不足,构建了地理空间视角下,兼顾动态目标在地理场景下的属性、时空关系和语义信息的轨迹模型(trajectory model,Tra-Model),设计了视频与GIS协同的交通违规行为分析方法,基于轨迹与规则几何约束条件对目标逆行、压线、禁止进入3类违规情况进行实时检测。以某高校为实验场地,分析不同交通场景下目标的3类违规情况。实验结果表明：（1）Tra-Model模型提取的轨迹包含目标类型、轨迹序列等语义信息,相比于现有动态目标跟踪算法,精准率提高15.6%;(2)所提方法对多个摄像机序列违规分析准确率均在70%以上,相对于现有方法具有更好的性能;（3）实现了地理场景下多种交通违规行为综合分析的全局性、高精度和探测类型多样性。     

融合像素—多尺度区域特征的高分辨率遥感影像分类算法

针对基于像素多特征的高分辨率遥感影像分类算法的"胡椒盐"现象和面向对象影像分析方法的"平滑地物细节"现象,提出了一种融合像素特征和多尺度区域特征的高分辨率遥感影像分类算法。(1)首先采用均值漂移算法对原始影像进行初始过分割,然后对初始过分割结果进行多尺度的区域合并,形成多尺度分割结果。根据多尺度区域合并RMI指数变化和分割尺度对分类精度的影响,确定最优分割尺度。(2)融合光谱特征、像元形状指数PSI(Pixel Shape Index)、初始尺度和最优尺度区域特征,并对多类型特征进行归一化,最后结合支持向量机(SVM)进行分类。实验结果表明该算法既能有效减少基于像素多特征的高分辨率遥感影像分类算法的"胡椒盐"现象,又能保持地物对象的完整性和地物细节信息,提高易混淆类别(如阴影和街道,裸地和草地)的分类精度。     

Speckle filtering of Synthetic Aperture Radar images using filters with object-size-adapted windows

Speckle degrades the radiometric quality of a Synthetic Aperture Radar (SAR) image. Previous methods for speckle reduction have used a fixed-size window for filtering the entire image. This, however, may not be effective for the entire image, as land covers of different sizes require different filtering windows. In this paper, a novel method is proposed by which each pixel in the image is filtered with a window appropriate for the size of object within it. The real in-phase and the imaginary quadrature components of the SAR images determine the best window size and the pixels in the intensity image are filtered using their own optimal windows. The proposed method is presented for both single- and multi-polarized SAR images, and the results of several common filters that were modified are presented. This approach is applied to two RADARSAT-2 images: one over San Francisco, California, USA and the other over St. John’s, Newfoundland and Labrador, Canada, producing results that were similar to, or outperformed, comparable filters while retaining details and suppressing speckle effectively. While the method was successful for single-look intensity data, it offers great potential for multi-look and amplitude data as well.