Table of Content

20 September 2017, Volume 46 Issue 9

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1'×1' Vertical Deflection and Its Precision Evaluation on China West Pacific Ocean Region

WANG Hubiao, WANG Yong, CAI Hua, BAO Lifeng

2017, 46(9):  1073-1079.  doi:10.11947/j.AGCS.2017.20160552

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Weighted-calcaulation method is designed by combining distance between observing points with height-measurement accuracy. With weighted least squares and the Vening-Meinesz formula,two 1'×1' digital vertical deflection grid models on a certain West Pacific Ocean region (0°N-40°N,105°E-145°E) are respectively constructed by use of multiple altimetry data and gravity anomaly,and the two models are compared to EGM2008 on two chosen typical regions. The results show that, the prime vertical component η is slightly larger than the meridian component ξ, and the root mean square error of derived vertical deflection on Southern China Sea where there is the complex seafloor topography is larger than the middle of West Pacific ocean. In addition, the root mean square error of two constructed models are generally less than 1.6".

Thermoelastic Seasonal Deformation in Chinese Mainland

TAN Weijie, XU Xueqing, DONG Danan, CHEN Junping, WU Bin

2017, 46(9):  1080-1087.  doi:10.11947/j.AGCS.2017.20160628

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In this paper, we explore the thermoelastic seasonal deformation in Chinese mainland based on the 260 GPS sites of crustal movement observation network of China (CMONOC). The results show that the change of land surface temperature can induce remarkable surface deformation in China. The most affected site is HLAR in Inner Mongolia, China. Its seasonal amplitude of surface deformation is about~2.293mm. and the site HIYS in Hainan is the least affected. The seasonal amplitude of surface deformation is about~0.177mm. Applying the thermoelastic seasonal deformation information in GRACE data analysis and the Mass loading models (MODEL), refined three-dimensional seasonal deformation map are derived. Taking GPS measurements as references, refined results show that the annual deformation derived from the MODEL and the GRACE data have been improved by about 6%,6%,2%;16%,5%,15% in the east, north and height components respectively.

Recovery of the Earth's Gravity Field Based on Spaceborne Atom-interferometry and Its Accuracy Estimation

ZHU Zhu, ZHAO Yanbin, LIAO He, TU Haibo, ZHANG Guowan, WEI Xiaogang

2017, 46(9):  1088-1097.  doi:10.11947/j.AGCS.2017.20170101

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The electrostatic gravity gradiometer has been successfully applied as a core sensor in satellite gravity gradiometric mission GOCE, and its observations are used to recover the Earth's static gravity field with a degree and order above 200. The lifetime of GOCE has been over, and the next generation satellite gravity gradiometry with higher resolution is urgently required in order to recover the global steady-state gravity field with a degree and order of 200~360. High potential precision can be obtained in space by atom-interferometry gravity gradiometer due to its long interference time, and thus the atom-interferometry-based satellite gravity gradiometry has been proposed as one of the candidate techniques for the next satellite gravity gradiometric mission. In order to achieve the science goal for high resolution gravity field measurement in the future, a feasible scheme of atom-interferometry gravity gradiometry in micro-gravity environment is given in this paper, and the gravity gradient measurement can be achieved with a noise of 0.85mE/Hz^1/2. Comparison and estimation of the Earth's gravity field recovery precision for different types of satellite gravity gradiometry is discussed, and the results show that the satellite gravity gradiometry based on atom-interferometry is expected to provide the global gravity field model with an improved accuracy of 7~8cm in terms of geoid height and 3×10^-5 m/s² in terms of gravity anomaly respectively at a degree and order of 252~290.

Semi-supervised Spatial-spectral Discriminant Analysis for Hyperspectral Image Classification

HOU Banghuan, WANG Kun, YAO Minli, JIA Weimin, WANG Rong

2017, 46(9):  1098-1106.  doi:10.11947/j.AGCS.2017.20170121

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In order to make full use of the spatial information embedded in the hyperspectral image to improve the classification accuracy, a semi-supervised spatial-spectral discriminant analysis (S³DA) algorithm for hyperspectral image classification is proposed. According to the spatial consistency property of hyperspectral image, the intra-class scatter matrix infered from a little labeled samples preserves the spectral similarity of the same class pixels, while the spatial local pixel scatter matrix defined by the unlabeled spatial neighbors uncovers the spatial-domain local pixel neighborhood structures and the ground objects detailed distribution. The S³DA method not only maintains the spectral-domain separability of the data set, but also preserves the spatial-domain local pixel neighborhood structure, which promotes the compactness of the same class pixels or the spatial neighbor pixels in the projected subspace and enhances the classification performance. The overall classification accuracies respectively reach 81.50% and 71.77% on the PaviaU and Indian Pines data sets. Compared with the traditional spectral methods, the proposed method can effectively improve ground objects classification accuracy.

Monocular Vision Obstacle Detection Method Based on Radial Optical Flow for Rotor UAV

ZHANG Xiaodong, HAO Xiangyang, SUN Guopeng, XU Yali

2017, 46(9):  1107-1115.  doi:10.11947/j.AGCS.2017.20160510

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To solve the problem of traditional Pyramid LK optical flow algorithm's poor accuracy and adaptability for rotor UAV to detect obstacle in complex outdoor environment, a monocular autonomous real-time obstacle detection method based on radial optical flow is proposed. In the optical flow, the radial optical flow is computed by fusing Pyramid LK optical flow with tangential optical flow, and a new obstacles decision strategy to detect obstacles based on the radial optical flow is put forward. Experimental results show that without increasing the complexity of algorithm, the proposed method can get a higher accuracy and better adaptability than traditional Pyramid LK algorithm, which can meet the requirements of UAV autonomous obstacle avoidance.

An Algorithm of Building Extraction in Urban Area Based on Improved Top-hat Transformations and LBP Elevation Texture

HE Manyun, CHENG Yinglei, QIU Langbo, ZHAO Zhongyang

2017, 46(9):  1116-1122.  doi:10.11947/j.AGCS.2017.20170158

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Classification of building and vegetation is difficult solely by LiDAR data and vegetation in shadows can't be eliminated only by aerial images. The improved top-hat transformations and local binary patterns (LBP) elevation texture analysis for building extraction are proposed based on the fusion of aerial images and LiDAR data. Firstly, LiDAR data is reorganized into grid cell, the algorithm removes ground points through top-hat transform. Then, the vegetation points are extracted by normalized difference vegetation index (NDVI). Thirdly, according to the elevation information of LiDAR points, LBP elevation texture is calculated and achieving precise elimination of vegetation in shadows or surrounding to the buildings. At last, morphological operations are used to fill the holes of building roofs, and region growing for complete building edges. The simulation is based on the complex urban area in Vaihingen benchmark provided by ISPRS, the results show that the algorithm affording higher classification accuracy.

Accurate and Automatic Building Roof Extraction Using Neighborhood Information of Point Clouds

ZHAO Chuan, ZHANG Baoming, CHEN Xiaowei, GUO Haitao, LU Jun

2017, 46(9):  1123-1134.  doi:10.11947/j.AGCS.2017.20160518

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High accuracy building roof extraction from LiDAR data is the key to build topological relationship of building roofs and reconstruct buildings. Aiming at the poor adaptation and low extraction precision of existing roof extraction methods for complex building, an accurate and automatic building roof extraction method using neighborhood information of point clouds is proposed. Point clouds features are calculated by principle component analysis, and reliable seed points are selected after feature histogram construction. Initial roof surfaces are extracted quickly and precisely by the proposed local normal vector distribution density-based spatial clustering of applications with noise (LNVD-DBSCAN). Roof competition problem is solved effectively by the poll model based on neighborhood information. Experimental results show that the proposed method can extract building roofs automatically and precisely, and has preferable adaptation to buildings with different complexity, which is able to provide reliable roof information for building reconstruction.

Satellite Video Point-target Tracking in Combination with Motion Smoothness Constraint and Grayscale Feature

WU Jiaqi, ZHANG Guo, WANG Taoyang, JIANG Yonghua

2017, 46(9):  1135-1146.  doi:10.11947/j.AGCS.2017.20160599

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In view of the problem of satellite video point-target tracking, a method of Bayesian classification for tracking with the constraint of motion smoothness is proposed, which named Bayesian MoST. The idea of naive Bayesian classification without relying on any prior probability of target is introduced. Under the constraint of motion smoothness, the gray level similarity feature is used to describe the likelihood of the target. And then, the simplified conditional probability correction model of classifier is created according to the independence assumption Bayes theorem. Afterwards, the tracking target position can be determined by estimating the target posterior probability on the basis of the model. Meanwhile, the Kalman filter, an assistance and optimization method, is used to enhance the robustness of tracking processing. The theoretical method proposed are validated in a number of six experiments using SkySat and JL1H video, each has two segments. The experiment results show that the BMoST method proposed have good performance, the tracking precision is about 90% and tracking trajectory is smoothing. The method could satisfy the needs of the following advanced treatment in satellite video.

Remote Sensing Image Change Detection Based on the Combination of Pixel-level and Object-level Analysis

FENG Wenqing, SUI Haigang, TU Jihui, SUN Kaimin

2017, 46(9):  1147-1155.  doi:10.11947/j.AGCS.2017.20160606

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In order to improve the change detection accuracy of the high resolution remote sensing image, a novel framework based on the combination of pixel-level and object-level analysis is proposed. Firstly, the two temporal images are superimposed, and the principal component analysis is performed. Then, it is utilized that the entropy rate segmentation algorithm to segment the first principal component image by changing the number of super-pixels to obtain the multi-layer super-pixel regions with different sizes. At the same time, by analyzing the difference of spectral feature and texture feature on two temporal images, it is used that adaptive PCNN neural network algorithm to make a fusion of the two difference images. Afterwards, the level set (CV) method is used to get the pixel-level change detection results. At last, the change intensity level quantization and decision level fusion are used on the initial change detection results with the region labeling matrix, serving as the post-processing part to obtain the changed objects. Experimental results on the sets of SPOT-5 multi-spectral images show that the new framework can effectively integrate the advantages of pixel-based and object-based image analysis methods, which can further improve the stability and applicability of the change detection process.

A Study of Sentinel-1 TOPS Mode Co-registration

WU Wenhao, ZHOU Zhiwei, LI Tao, LONG Sichun

2017, 46(9):  1156-1164.  doi:10.11947/j.AGCS.2017.20160352

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The TOPS imaging mode is the default operation mode of Sentinel-1 satellite, an overall azimuth coregistration accuracy of better than 0.001 pixels is required for this configuration in order to achieve the interferometric phase bias is less than three degrees. Based on the high accuracy of Sentinel-1 orbital information, this paper demonstrates a sufficiently high coregistration accuracy is able to be achieved by geometrical coregistration algorithm, which satisfies the pre-requirement for estimating the residual coregistration error by enhanced spectral diversity method. Based on DORIS open source software, a coregistration approach for Sentinel-A TOPS mode is implemented by an algorithm of geometric prediction of the shifts using precise orbit information, and an improvement on coregistration processing is achieved by enhanced spectral diversity. An interferometric phase jump between two Bursts could be caused by surface deformation in azimuth direction, and introduce a disturbance when estimating the residual coregistration error by enhanced spectral diversity method. In this paper, based on related theory analysis and real data processing test, an outlier detection estimation method is proposed to reduce the disturbance of enhanced spectral diversity coregistration method, which is caused by phase jumps.

Edge Extraction Algorithm of SAR Image Using Random Direction Symmetric Difference Kernel

WANG Dailiang, LI Yu, LIN Wenjie, ZHAO Quanhua

2017, 46(9):  1165-1173.  doi:10.11947/j.AGCS.2017.20160401

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Due to the noise sensitivity and limited directivity of extracted edge presented in current edge detection algorithms, it is difficult to effectively extract the edges with any direction between the two regions with similar intensities from SAR images. In this paper, an edge extraction algorithm of SAR image using two symmetric windows is proposed. The position of grid point of any pixel in SAR image is employed as a symmetric center, then symmetric windows in any direction are constructed by the symmetric center. The kernel function of distances from the central pixel to pixels in each window is defined, then the weighted averages of pixel spectral measurements are calculated for the two symmetric windows, respectively. The absolute value of difference between above averages is employed as edge degree of the central pixel on this direction, and maximum degree from all directions is selected to judge the pixel as an edge pixel. To delete error edge pixels extracted, post-processing procedure based on filtering operation is designed. The interferences of speckle noises are overcome to some extent and edges in random direction are extracted accurately by the proposed algorithm, respectively, which is shown by qualitative and quantitative analysis of the edge extraction results from analog images.

Weighted Exponential Region Energy Model for River Segmentation of SAR Images

HAN Bin, WU Yiquan

2017, 46(9):  1174-1181.  doi:10.11947/j.AGCS.2017.20170134

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The traditional active contour models can hardly achieve the accurate river segmentation of SAR images. To solve this problem, a novel active contour model with weighted exponential region energy is proposed, which can extract rivers in SAR images accurately. The exponential region energy is incorporated into the energy functional of the Chan-Vese model, which can measure the difference between the segmented image and the original image, resulting in the improvement of segmentation accuracy of the model. In addition, the maximum absolute differences of the pixel grayscale values inside the object and background regions are utilized to replace the original constant region energy weights, which can adaptively adjust the ratios of the object and background region energies and accelerate the motion of the curve towards the boundaries of the object region, resulting in the higher segmentation efficiency. The experiments are performed on real SAR images of rivers and results demonstrate that compared with the traditional active contour models, the proposed model can segment rivers in SAR images more rapidly and accurately and has some advantages in terms of both segmentation performance and segmentation efficiency.

More Rigorous Correction of Refraction Effects in Two-media Stereophoto-grammetry

CAO Bin, ZHU Shulong, QIU Zhenge, CAO Bincai

2017, 46(9):  1182-1192.  doi:10.11947/j.AGCS.2017.20170119

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A more rigorous algorithm is presented for correction of refraction effects in two-media stereo photogrammetry. The mid-point of the shortest line segment joining two aerial corresponding rays of a point on an underwater object is used as a photogrammetric intersection point which doesn't exist when the two rays are non-intersecting. As a result, the uncertainty of the intersection point is removed, the positional relationship between the intersection point and the true object point becomes definite, and the refraction correction formula from the intersection point to the true object point can be strictly derived. The bad effect on the refraction correction is firstly analyzed, which caused by that the two rays are non-intersecting. Then the positional relationship between the intersection point and the true object point is studied. After that, the formulas regarding water depth and geodetic coordinates of points on an underwater object are deduced, that is often known as correction of refraction effects. Finally, the algorithm is tested by two experiments using the data of WorldView-2. The results show that the algorithm is suitable for any case in which whether or not the two aerial corresponding rays of an underwater object point are intersecting, and it can significantly improve the measurement accuracy of underwater object's elevation.

GPU Parallel Bundle Block Adjustment

ZHENG Maoteng, ZHOU Shunping, XIONG Xiaodong, ZHU Junfeng

2017, 46(9):  1193-1201.  doi:10.11947/j.AGCS.2017.20160636

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To deal with massive data in photogrammetry, we introduce the GPU parallel computing technology. The preconditioned conjugate gradient and inexact Newton method are also applied to decrease the iteration times while solving the normal equation. A brand new workflow of bundle adjustment is developed to utilize GPU parallel computing technology. Our method can avoid the storage and inversion of the big normal matrix, and compute the normal matrix in real time. The proposed method can not only largely decrease the memory requirement of normal matrix, but also largely improve the efficiency of bundle adjustment. It also achieves the same accuracy as the conventional method. Preliminary experiment results show that the bundle adjustment of a dataset with about 4500 images and 9 million image points can be done in only 1.5 minutes while achieving sub-pixel accuracy.

The Study of the Key Techniques in the Realization of Integrated Engineering Survey System in South-to-north Water Diversion Project

WANG Haicheng

2017, 46(9):  1202-1202.  doi:10.11947/j.AGCS.2017.20170172

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Theory and Method of Measurement Data Fitting and Its Application in Component Modeling

XIANG Wei

2017, 46(9):  1203-1203.  doi:10.11947/j.AGCS.2017.20170206

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Study on Theory and Method of GNSS Integer Least Squares Ambiguity Resolution

LU Liguo

2017, 46(9):  1204-1204.  doi:10.11947/j.AGCS.2017.20170416

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Perceptual Hashing Based Authentication Algorithm Research for Remote Sensing Image

DING Kaimeng

2017, 46(9):  1205-1205.  doi:10.11947/j.AGCS.2017.20170233

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Intelligent Analysis and Prediction of Mine Slope Deformation Monitoring Data Based on Gaussian Process

WANG Jianmin

2017, 46(9):  1206-1206.  doi:10.11947/j.AGCS.2017.20170143

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