Automatic Registration Between Low-Altitude LiDAR Point Clouds and Aerial Images Using Road Features

Among the many means of acquiring surface information, low-altitude light detection and ranging (LiDAR) systems (e.g., unmanned aerial vehicle LiDAR, UAV-LiDAR) have become an important approach to accessing geospatial information. Considering the lower level of hardware technology in low-altitude LiDAR systems compared to that in airborne LiDAR, and the greater flexibility in-flight, registration procedures must be first performed to facilitate the fusion of laser point data and aerial images. The corner points and edges of buildings are frequently used for the automatic registration of aerial imagery with LiDAR data. Although aerial images and LiDAR data provide powerful support for building detection, adaptive edge detection for all types of building shapes is difficult. To deal with the weakness of building edge detection and reduce matching-related computation, the study presents a novel automatic registration method for aerial images, with LiDAR data, on the basis of main-road information in urban areas. Firstly, vector road centerlines are extracted from raw LiDAR data and then projected onto related aerial images with the use of coarse exterior orientation parameters (EOPs). Secondly, the corresponding image road features of each LiDAR vector road are determined using an improved total rectangle-matching approach. Finally, the endpoints of the conjugate road features obtained from the LiDAR data and aerial images are used as ground control points in space resection adjustment to refine the EOPs; an iterative strategy is used to obtain optimal matching results. Experimental results using road features verify the feasibility, robustness and accuracy of the proposed approach.     

基于小波变换的大面阵CCD相机影像亮度不一致性消除算法

针对大面阵CCD影像亮度不均匀现象，提出一种基于小波变换的影像亮度不一致性消除算法。在分析像面光照模型的基础上，构造出光照模型的仿真影像，通过分析仿真影像的小波变换系数，发现影像亮度不一致信息集中反映在小波的近似系数之中。利用这一特性，先将数字相机原始影像进行多尺度小波分解，并对近似系数取对数，然后施加一个衰减算子，对近似系数的对数进行非均匀改正，将改正后的系数取指数，再对近似系数进行线性拉伸，同时根据人类视觉系统对不同方向细节敏感度的不同，对不同方向的细节系数进行不同幅度的线性拉伸，以突出图像细节，最后通过影像重建，获得均匀亮度的航空影像。实验结果显示，该算法具有很好的匀光效果，同时能够较好地保持影像细节特征。     

甘肃北山古火山机构浅见

甘肃北山地区基岩裸露好, 古生代的火山岩系在区内广泛发育, 这就给用遥感技术寻找和研究古火山机构提供了有利条件。本文通过对北山地区卫星MSS像片、全色航空像片的解译, 阐述了锰铁山、黑鹰山古火山机构的形态、地貌、水系等遥感影像特征以及古火山机构与构造、矿产的关系。北山地区古火山机构的发现, 对类似地区用遥感方法寻找古火山机构及与古火山机构有关的矿产提供了例证。     

Delineation and geometric modeling of road networks

In this work we present a novel vision-based system for automatic detection and extraction of complex road networks from various sensor resources such as aerial photographs, satellite images, and LiDAR. Uniquely, the proposed system is an integrated solution that merges the power of perceptual grouping theory (Gabor filtering, tensor voting) and optimized segmentation techniques (global optimization using graph-cuts) into a unified framework to address the challenging problems of geospatial feature detection and classification.Firstly, the local precision of the Gabor filters is combined with the global context of the tensor voting to produce accurate classification of the geospatial features. In addition, the tensorial representation used for the encoding of the data eliminates the need for any thresholds, therefore removing any data dependencies.Secondly, a novel orientation-based segmentation is presented which incorporates the classification of the perceptual grouping, and results in segmentations with better defined boundaries and continuous linear segments.Finally, a set of gaussian-based filters are applied to automatically extract centerline information (magnitude, width and orientation). This information is then used for creating road segments and transforming them to their polygonal representations.     

自动空中三角测量系统开发及精度分析

在传统解析空中三角测量理论的基础上,运用数字摄影测量、数字图像处理、误差处理等理论,用VC＋＋开发自动空中三角测量程序的主要功能,并用本程序对一个实验测区进行空中三角测量处理,对实验结果做了分析,最后实践证明,利用GPS/IMU数据辅助空中三角测量,能达到较高的自动化程度。     

航空摄影测量中立体模型的重建(英文)

This paper describes the operational issues and basic technical requirements of modern aerial photogrammetry. The accuracy of photogrammetric point determination and the y-parallax at corresponding model points is analyzed when stereo models are reconstituted by using the exterior orientation elements of aerial images. Real aerial photographs, at image scales from 1：2 500 to 1：6 0000, with DGPS/IMU data taken from various topographies in China were processed by our POS-supported bundle block adjustment program WuCAPS. The empirical results verified that the accuracy of the exterior orientation elements from bundle block adjustment meets the requirements of the specifications of topographic mapping. However, the accuracy of the exterior orientation elements determined by POS fails to meet the requirements of the specifications of topographic mapping.     

复杂背景下航拍图像的电力线自动提取算法

无人机对电力线巡检的关键问题是如何从复杂背景的航拍图像中准确地提取电力线。本文提出了一种基于二维变分模态分解 (2D-VMD) 提取电力线的新算法。首先对原始航拍图像进行预处理,加快数据处理速度;然后采用2D-VMD算法对预处理后的图像进行分解,通过改进后的点锐度算法,选取带有电力线特征的IMF分量图,并利用Roberts算子进行边缘检测;最后利用形态学改进的Hough变换,完成对电力线的提取。试验结果表明,本文方法比传统的Canny算子结合Hough变换方法、LSD方法、Roberts 算法结合形态学改进的Hough变换方法更具精确性、抗噪性、自动化。     

轮廓波变换在遥感目标图像检索中的应用

除具有纹理属性外,遥感图像中还包含大量的结构性边缘特征。如何有效捕捉这些特征中的信息进行检索,成为提高遥感图像检索效率的关键。依据Contourlet在离散域的多尺度几何分析的功能,提出一种利用Contourlet子带能量分布特性提取原始图像在多个尺度下的边缘方向信息进行检索的方法。针对Cont-ourlet变换响应不同特征方向能力的差别,采用正交补偿法加以改正,经过傅里叶算子的处理,从而实现旋转不变结构性边缘特征的检索。最后,在遥感目标图像上所作的实验证实了该算法的有效性。     

基于图像匹配的机载遥感影像质量自动检查方法研究

航空遥感平台和技术的发展,促进了航空遥感影像在基础地理信息获取、国土监测、环境监测、应急救灾等各个领域中的应用。同时,航空遥感系统对飞行环境、气候气象反应较为灵敏,遥感影像质量的检查十分重要。本文系统地阐述了航空遥感影像质量中旋转角、航向重叠率、旁向重叠率、航带生成等参数的计算理论与方法,该方法是适应数字遥感影像的现状上提出的,并且通过自行开发的系统对算法的可行性和有效性进行验证。本文利用2009年6月机载遥感系统拍摄的1400多张影像进行实验。实验结果表明技术方法、软件系统都较为有效,达到机载遥感影像质量自动检查要求。     

Photo Orientation Under Unstable Conditions: A Robust Trial and Error Approach Using Range Ratios

Relative orientation is one of the fundamental steps in forming a photogrammetric model. Whilst relative orientation is straightforward in most cases of aerial photogrammetry this may not be the case in close range photogrammetry where the nature of the photographs and the cameras being used often raise unfamiliar problems. This paper addresses the problem of performing relative orientation of non-metric photographs under unstable conditions where there are no ground control points and the ray intersection geometry is poor. The relative orientation problem is approached from several viewpoints, including a method that relies on little information about the exterior or relative orientation parameters. The solution is based on an iterative process, in which a set of three virtual control points (VCPs) is created, using photo coordinates and range ratios. The validity of the VCPs is checked during every iteration by an estimation of the coplanarity condition using two or more conjugate checkpoints. During the iteration a database is formed, which is then used to obtain a net of VCPs that fulfil the coplanarity condition for the checkpoints. The VCPs are then used to compute the "relative" exterior orientation by space resection. The proposed method was tested on both simulated and real photographs and was found to have some advantages over more commonly used techniques.     

Satellite/Aerial Image Compression Using Adaptive Block Truncation Coding Technique

Satellite/aerial images taken from high altitude contain large amount of pixels to store accurate information. These high resolution images require large storage capacity and more transmission time. Applying an efficient compression technique on these images can reduce high storage capacity requirement and transmission time. In this paper block truncation coding (BTC) based color image compression technique for aerial/satellite images is proposed. High degree of correlation among the RGB planes of a color image can be reduced by converting these planes into HSV planes. Each of the H and S planes are encoded using BTC with quad clustering and V plane is encoded with BTC based bi-clustering or tri-clustering depending on the edge information present in the plane. The effectivity of the proposed method is validated by comparing it with the conventional BTC and its variant methods. Experimental analysis indicate that the proposed method is superior to other state of the art methods both in terms of visual quality and quantitative metrics.     

GNSS辅助摄影测量中几个问题的探讨

GNSS辅助摄影测量是在数字摄影测量基础上发展起来的一种技术手段。它使航空摄影、像片控制点布设、外方位元素的获取和空中三角测量进入了一个新时代。本文对航摄分区和补摄、区域划分以及像控点布设应注意的问题进行了探讨,同时,对应用前景进行了概述。     

Preparation of optimal land use maps for agricultural development using remote sensing techniques

Optimal land use map of Kanholi area, part of Nagpur district,Maharashtra have been prepared using Satellite imagery in 1:1000,000 and 1:250,000 and aerial photographs in 1:60,000 scale with adequate ground checks. The Satellite imagery proved valuable information about landscape characteristics, land use, hydrology and other environmental features. The aerial photographs were used to prepare comparatively large scale land resource association maps in scale 1:60,000 on geomorphology, landuse, soil hydrology. Soil irrigability, land irrigability and land capability maps are also attempted after interpreting soils information collected during field studies. The utility of this technique in preparation of optimal land use map with associated limitations due to scale have been discussed in the paper.     

Geological interpretation of radar images

Side-looking airborne radar systems (SLAR), which produce fair quality images of the earth’s surface, have been developed over the past twenty years. These systems provide synoptic information over large areas with great speed. In regions where constant cloud cover prevents or hampers aerial photography, radar can be a source of valuable information: however, in less adverse weather conditions and at larger scales single radar images, until quite recently the normal presentation, cannot compete with conventional, stereoscopically viewed aerial photographs. It has now become common practice to take parallel strips with a large, 30–60%, overlap and scanned from the same direction. In this way a stereoscopic effect may be obtained, which considerably improves the interpretation possibilities of such radar images. The same analytical techniques used in photo-geology can also be applied to radar-interpretation. In order to obtain optimal results, the geologist who interprets radar images should have some understanding of radar operation.     

“针孔”模拟成像下的单航空影像与LiDAR点云配准

以摄影测量共线方程为严格配准模型,提出了一种引入针孔成像模拟过程的单张航空影像LiDAR点云配准迭代方法,共分为3个阶段:第一,利用航空影像内参数及初始外方位元素对LiDAR点云针孔模拟成像,生成与航空影像空间分辨率、几何形变相接近且具有相同幅面大小的透视影像-LiDAR深度影像;第二,以梯度互信息作为影像相似性测度依据,实施影像金字塔、分块处理策略实现LiDAR深度影像与航空影像几何变换参数快速估计,进而依据估计参数及LiDAR深度影像、激光脚点投影关系建立LiDAR点云航空影像概略相关;第三,以LiDAR点云影像概略相关下的近似同名像点为观测值,以像点梯度互信息为权重,实施摄影测量空间后方交会计算获得优化的影像外方位元素,生成新的LiDAR深度影像并重复上述过程,直至满足给定的迭代计算条件,实现单张航空影像与LiDAR点云数据的自动空间配准。实验表明,本文方法配准精度达亚像素级且自动化程度高。     

基于向量场模型的多光谱遥感图像多尺度边缘检测

提出一种基于向量场模型的多光谱图像多尺度边缘检测算法,并在算法中引入两种梯度方向量化邻域模型。首先,对多光谱图像进行二进小波变换,得到每个波段图像在不同尺度上的细节系数,然后根据向量场模型计算多光谱图像的梯度幅值和梯度方向,选择适宜的邻域模型对梯度方向进行量化,最后沿量化后的方向获取由细到粗的多层次边缘信息。对QuickBird多光谱图像上农田、厂房等地物进行多尺度边缘提取,定性分析了图像分辨率大小与地物尺寸关系在不同尺度边缘信息的表征;利用F测度,定量评价了检测结果的边缘准确度。与传统算子检测结果对比表明,利用向量场模型综合了所有波段的边缘信息,减少了多波段图像边缘信息的不一致性,引入的量化邻域模型能够有效地获取完整的多尺度边缘点。     

影像镶嵌重采样算法的选择

在佛山市1∶8000原始航片数字影像镶嵌图的生产过程中,发现镶嵌成果与原始影像相比,信息丢失严重。探讨了这种现象产生的原因,比较了各种重采样算法对镶嵌成果的影响,最后通过选择合适的重采样算法解决了此问题。     

Aerial photo-interpretation techniques for appraisal of house density tested on Bikaner city,India

In this paper house density has been calculated on medium scale photographs and efforts have been made to recognize the physical characteristics of houses on aerial photographs for the purpose of house density mapping. Although the aerial photographs reveal wealth of information regarding the houses, only the residential plots as house units have been taken into account for the present study.     

Application of drone for landslide mapping,dimension estimation and its 3D reconstruction

Dimension estimation of landslides is a major challenge while preparing the landslide inventory map, for which very high-resolution satellite data/aerial photography is required, which is very expensive. An alternative is the application of drones for such mapping. This study presents the utility of drone/unmanned aerial vehicle (UAV) for mapping and 3D reconstruction of two landslides near IIT Mandi, Himachal Pradesh. In this study, we used DJI Phantom 3 Advanced drone to collect high-resolution images of landslides. Features in the images were automatically detected, described, and matched among photographs using scale invariant feature transform (SIFT) technique. The 3D position and orientation of the cameras and the XYZ location of each feature in the photographs was estimated using bundle block adjustment. This resulted in sparse 3D point cloud, which was densified using Clustering View for Multi-View Stereo (CMVS) algorithm. Finally, surface reconstruction was done using Poisson Surface Reconstruction method, which was visualised in open source software CloudCompare. The 3D model, generated from drone images, was validated using field measurements of some objects, and 3D surface created from total station. Various quantities i.e. width (length), height and perimeter were measured in the 3D drone model and verified with total station data. The differences among all the measured quantities for both the landslides are less than 5% keeping the measurements of total station as reference. The 3D reconstructed from the sets of photographs is very accurate giving the measurements up to cm level and even small objects could be easily identified. In addition, digital elevation model (DEM) of sub meter resolution could be easily generated and used for various applications. Hence drone-based imagery in combination with 3D scene reconstruction algorithms provide flexible and effective tools to map and monitor landslide apart from accurately assessing the dimensions of the landslides.