A General Framework of Remote Sensing Epipolar Image Generation

Epipolar images can improve the efficiency and accuracy of dense matching by restricting the search range of correspondences from 2-D to 1-D, which play an important role in 3-D reconstruction. As most of the satellite images in archives are incidental collections, which do not have rigorous stereo properties, in this paper, we propose a general framework to generate epipolar images for both in-track and cross-track stereo images. We first investigate the theoretical epipolar constraints of single-sensor and multi-sensor images and then introduce the proposed framework in detail. Considering large elevation changes in mountain areas, the publicly available digital elevation model (DEM) is applied to reduce the initial offsets of two stereo images. The left image is projected into the image coordinate system of the right image using the rational polynomial coefficients (RPCs). By dividing the raw images into several blocks, the epipolar images of each block are parallel generated through a robust feature matching method and fundamental matrix estimation, in which way, the horizontal disparity can be drastically reduced while maintaining negligible vertical disparity for epipolar blocks. Then, stereo matching using the epipolar blocks can be easily implemented and the forward intersection method is used to generate the digital surface model (DSM). Experimental results on several in-track and cross-track images, including optical-optical, SAR-SAR, and SAR-optical pairs, demonstrate the effectiveness of the proposed framework, which not only has obvious advantages in mountain areas with large elevation changes but also can generate high-quality epipolar images for flat areas. The generated epipolar images of a ZiYuan-3 pair in Songshan are further utilized to produce a high-precision DSM.

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A DETAILED STUDY ABOUT DIGITAL SURFACE MODEL GENERATION USING HIGH RESOLUTION SATELLITE STEREO IMAGERY

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-iii-1-69-2016 ◽

2016 ◽

Vol III-1 ◽

pp. 69-76 ◽

Cited By ~ 3

Author(s):

K. Gong ◽

D. Fritsch

Keyword(s):

High Resolution ◽

Stereo Matching ◽

Research Area ◽

Surface Model ◽

Polynomial Coefficients ◽

Rational Polynomial ◽

Dense Stereo Matching ◽

Stereo Imagery ◽

Satellite Sensors ◽

High Resolution Satellite Imagery

Photogrammetry is currently in a process of renaissance, caused by the development of dense stereo matching algorithms to provide very dense Digital Surface Models (DSMs). Moreover, satellite sensors have improved to provide sub-meter or even better Ground Sampling Distances (GSD) in recent years. Therefore, the generation of DSM from spaceborne stereo imagery becomes a vivid research area. This paper presents a comprehensive study about the DSM generation of high resolution satellite data and proposes several methods to implement the approach. The bias-compensated Rational Polynomial Coefficients (RPCs) Bundle Block Adjustment is applied to image orientation and the rectification of stereo scenes is realized based on the Project-Trajectory-Based Epipolarity (PTE) Model. Very dense DSMs are generated from WorldView-2 satellite stereo imagery using the dense image matching module of the C/C++ library LibTsgm. We carry out various tests to evaluate the quality of generated DSMs regarding robustness and precision. The results have verified that the presented pipeline of DSM generation from high resolution satellite imagery is applicable, reliable and very promising.

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Accurate hierarchical stereo matching based on 3D plane labeling of superpixel for stereo images from rovers

International Journal of Advanced Robotic Systems ◽

10.1177/17298814211002113 ◽

2021 ◽

Vol 18 (2) ◽

pp. 172988142110021

Author(s):

Haichao Li ◽

Zhi Li ◽

Jianbin Huang ◽

Bo Meng ◽

Zhimin Zhang

Keyword(s):

Large Scale ◽

Stereo Matching ◽

State Of The Art ◽

The State ◽

Normal Vector ◽

Stereo Images ◽

Disparity Map ◽

Matching Method ◽

Search Range ◽

Coarse To Fine

An accurate hierarchical stereo matching method is proposed based on continuous 3D plane labeling of superpixel for rover’s stereo images. This method can infer the 3D plane label of each pixel combined with the slanted-patch matching strategy and coarse-to-fine constraints, which is especially suitable for large-scale scene matching with low-texture or textureless regions. At every level, the stereo matching method based on superpixel segmentation makes the iteration convergence faster and avoids huge redundant computations. In the coarse-to-fine matching scheme, we propose disparity constraint and 3D normal vector constraint between adjacent levels through which the disparity map and 3D normal vector map at a coarser level are used to restrict the search range of disparity and normal vector at a fine level. The experimental results with the Chang’e-3 rover dataset and the KITTI dataset show that the proposed stereo matching method is efficiently and accurately compared with the state-of-the-art 3D labeling algorithm, especially in low-texture or textureless regions. The computational efficiency of this method is about five to six times faster than the state-of-the-art 3D labeling method, and the accuracy is better.

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A DETAILED STUDY ABOUT DIGITAL SURFACE MODEL GENERATION USING HIGH RESOLUTION SATELLITE STEREO IMAGERY

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iii-1-69-2016 ◽

2016 ◽

Vol III-1 ◽

pp. 69-76

Author(s):

K. Gong ◽

D. Fritsch

Keyword(s):

High Resolution ◽

Stereo Matching ◽

Research Area ◽

Surface Model ◽

Polynomial Coefficients ◽

Rational Polynomial ◽

Dense Stereo Matching ◽

Stereo Imagery ◽

Satellite Sensors ◽

High Resolution Satellite Imagery

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Matching Large Baseline Oblique Stereo Images Using an End-to-End Convolutional Neural Network

Remote Sensing ◽

10.3390/rs13020274 ◽

2021 ◽

Vol 13 (2) ◽

pp. 274

Author(s):

Guobiao Yao ◽

Alper Yilmaz ◽

Li Zhang ◽

Fei Meng ◽

Haibin Ai ◽

...

Keyword(s):

Neural Network ◽

Deep Learning ◽

Convolutional Neural Network ◽

Stereo Matching ◽

Least Square ◽

Affine Invariant ◽

Stereo Images ◽

Distance Ratio ◽

Matching Algorithm ◽

End To End

The available stereo matching algorithms produce large number of false positive matches or only produce a few true-positives across oblique stereo images with large baseline. This undesired result happens due to the complex perspective deformation and radiometric distortion across the images. To address this problem, we propose a novel affine invariant feature matching algorithm with subpixel accuracy based on an end-to-end convolutional neural network (CNN). In our method, we adopt and modify a Hessian affine network, which we refer to as IHesAffNet, to obtain affine invariant Hessian regions using deep learning framework. To improve the correlation between corresponding features, we introduce an empirical weighted loss function (EWLF) based on the negative samples using K nearest neighbors, and then generate deep learning-based descriptors with high discrimination that is realized with our multiple hard network structure (MTHardNets). Following this step, the conjugate features are produced by using the Euclidean distance ratio as the matching metric, and the accuracy of matches are optimized through the deep learning transform based least square matching (DLT-LSM). Finally, experiments on Large baseline oblique stereo images acquired by ground close-range and unmanned aerial vehicle (UAV) verify the effectiveness of the proposed approach, and comprehensive comparisons demonstrate that our matching algorithm outperforms the state-of-art methods in terms of accuracy, distribution and correct ratio. The main contributions of this article are: (i) our proposed MTHardNets can generate high quality descriptors; and (ii) the IHesAffNet can produce substantial affine invariant corresponding features with reliable transform parameters.

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Disparity estimation using Graph cuts for road applications

E3S Web of Conferences ◽

10.1051/e3sconf/202129701055 ◽

2021 ◽

Vol 297 ◽

pp. 01055

Author(s):

Mohamed El Ansari ◽

Ilyas El Jaafari ◽

Lahcen Koutti

Keyword(s):

Stereo Matching ◽

Optimal Solution ◽

Similarity Criterion ◽

Graph Cuts ◽

Search Space ◽

Disparity Estimation ◽

Stereo Images ◽

Disparity Map ◽

Current Frame ◽

Edge Points

This paper proposes a new edge based stereo matching approach for road applications. The new approach consists in matching the edge points extracted from the input stereo images using temporal constraints. At the current frame, we propose to estimate a disparity range for each image line based on the disparity map of its preceding one. The stereo images are divided into multiple parts according to the estimated disparity ranges. The optimal solution of each part is independently approximated via the state-of-the-art energy minimization approach Graph cuts. The disparity search space at each image part is very small compared to the global one, which improves the results and reduces the execution time. Furthermore, as a similarity criterion between corresponding edge points, we propose a new cost function based on the intensity, the gradient magnitude and gradient orientation. The proposed method has been tested on virtual stereo images, and it has been compared to a recently proposed method and the results are satisfactory.

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Geometric Accuracy Assessment of Deimos-2 Panchromatic Stereo Pairs: Sensor Orientation and Digital Surface Model Production

Sensors ◽

10.3390/s20247234 ◽

2020 ◽

Vol 20 (24) ◽

pp. 7234

Author(s):

Manuel A. Aguilar ◽

Rafael Jiménez-Lao ◽

Abderrahim Nemmaoui ◽

Fernando J. Aguilar

Keyword(s):

Urban Areas ◽

Satellite Images ◽

Accuracy Assessment ◽

Bare Soil ◽

Surface Model ◽

Stereo Pair ◽

Rational Polynomial ◽

Sensor Orientation ◽

Vertical Accuracy ◽

Land Covers

Accurate elevation data, which can be extracted from very high-resolution (VHR) satellite images, are vital for many engineering and land planning applications. In this way, the main goal of this work is to evaluate the capabilities of VHR Deimos-2 panchromatic stereo pairs to obtain digital surface models (DSM) over different land covers (bare soil, urban and agricultural greenhouse areas). As a step prior to extracting the DSM, different orientation models based on refined rational polynomial coefficients (RPC) and a variable number of very accurate ground control points (GCPs) were tested. The best sensor orientation model for Deimos-2 L1B satellite images was the RPC model refined by a first-order polynomial adjustment (RPC1) supported on 12 accurate and evenly spatially distributed GCPs. Regarding the Deimos-2 based DSM, its completeness and vertical accuracy were compared with those obtained from a WorldView-2 panchromatic stereo pair by using exactly the same methodology and semiglobal matching (SGM) algorithm. The Deimos-2 showed worse completeness values (about 6% worse) and vertical accuracy results (RMSEZ 42.4% worse) than those computed from WorldView-2 imagery over the three land covers tested, although only urban areas yielded statistically significant differences (p < 0.05).

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Land-ice elevation changes from photon-counting swath altimetry: first applications over the Antarctic ice sheet

Journal of Glaciology ◽

10.3189/2015jog14j048 ◽

2015 ◽

Vol 61 (225) ◽

pp. 17-28 ◽

Cited By ~ 13

Author(s):

Duncan A. Young ◽

Laura E. Lindzey ◽

Donald D. Blankenship ◽

Jamin S. Greenbaum ◽

Alvaro Garcia De Gorordo ◽

...

Keyword(s):

Dynamic Change ◽

High Surface ◽

Photon Counting ◽

Ice Sheet ◽

Test Case ◽

Laser Altimeter ◽

Surface Slopes ◽

Elevation Changes ◽

The Alamo ◽

Cross Track

AbstractSatellite altimetric time series allow high-precision monitoring of ice-sheet mass balance. Understanding elevation changes in these regions is important because outlet glaciers along ice-sheet margins are critical in controlling flow of inland ice. Here we discuss a new airborne altimetry dataset collected as part of the ICECAP (International Collaborative Exploration of the Cryosphere by Airborne Profiling) project over East Antarctica. Using the ALAMO (Airborne Laser Altimeter with Mapping Optics) system of a scanning photon-counting lidar combined with a laser altimeter, we extend the 2003–09 surface elevation record of NASA’s ICESat satellite, by determining cross-track slope and thus independently correcting for ICESat’s cross-track pointing errors. In areas of high slope, cross-track errors result in measured elevation change that combines surface slope and the actual Δz/Δt signal. Slope corrections are particularly important in coastal ice streams, which often exhibit both rapidly changing elevations and high surface slopes. As a test case (assuming that surface slopes do not change significantly) we observe a lack of ice dynamic change at Cook Ice Shelf, while significant thinning occurred at Totten and Denman Glaciers during 2003–09.

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Near-Surface and Land Surface Forecast System of the Vancouver 2010 Winter Olympic and Paralympic Games

Journal of Hydrometeorology ◽

10.1175/2011jhm1250.1 ◽

2011 ◽

Vol 12 (4) ◽

pp. 508-530 ◽

Cited By ~ 26

Author(s):

Natacha B. Bernier ◽

Stéphane Bélair ◽

Bernard Bilodeau ◽

Linying Tong

Keyword(s):

High Resolution ◽

Land Surface ◽

Snow Depth ◽

Land Surface Model ◽

Surface Model ◽

Near Surface ◽

Elevation Changes ◽

Forecast Models ◽

Operational Models ◽

Paralympic Games

Abstract A high-resolution 2D near-surface and land surface model was developed to produce snow and temperature forecasts over the complex alpine region of the Vancouver 2010 Winter Olympic and Paralympic Games. The model is driven by downscaled operational outputs from the Meteorological Service of Canada’s regional and global forecast models. Downscaling is applied to correct forcings for elevation differences between the operational forecast models and the high-resolution surface model. The high-resolution near-surface and land surface model is then used to further refine the forecasts. The model was validated against temperature and snow depth observations. The largest improvements were found in regions where low-resolution (i.e., on the order of 10 km or more) operational models typically lack the spatial resolution to capture rapid elevation changes. The model was found to better reproduce the intermittent snow cover at low-lying stations and to reduce snow depth error by as much as 3 m at alpine stations.

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Using Unmanned Aerial Vehicle Remote Sensing and a Monitoring Information System to Enhance the Management of Unauthorized Structures

Applied Sciences ◽

10.3390/app9224954 ◽

2019 ◽

Vol 9 (22) ◽

pp. 4954

Author(s):

Yuanrong He ◽

Weiwei Ma ◽

Zelong Ma ◽

Wenjie Fu ◽

Chihcheng Chen ◽

...

Keyword(s):

Information System ◽

Unmanned Aerial Vehicle ◽

Aerial Images ◽

Surface Model ◽

Ground Survey ◽

Elevation Changes ◽

Aerial Vehicle ◽

New Construction ◽

Gis Software ◽

Interaction Interpretation

In this research, we investigated using unmanned aerial vehicle (UAV) photographic technology to prevent the further expansion of unauthorized construction and thereby reduce postdisaster losses. First, UAV dynamic aerial photography was used to obtain dynamic digital surface model (DSM) data and elevation changes of 2–8 m as the initial sieve target. Then, two periods of dynamic orthophoto images were superimposed for human–computer interaction interpretation, so we could quickly distinguish buildings undergoing expansion, new construction, or demolition. At the same time, mobile geographic information system (GIS) software was used to survey the field, and the information gathered was developed to support unauthorized construction detection. Finally, aerial images, interpretation results, and ground survey information were integrated and released on WebGIS to build a regulatory platform that can achieve accurate management and effectively prevent violations.

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RPC STEREO PROCESSOR (RSP) – A SOFTWARE PACKAGE FOR DIGITAL SURFACE MODEL AND ORTHOPHOTO GENERATION FROM SATELLITE STEREO IMAGERY

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-iii-1-77-2016 ◽

2016 ◽

Vol III-1 ◽

pp. 77-82 ◽

Cited By ~ 17

Author(s):

R. Qin

Keyword(s):

Software Package ◽

Large Scale ◽

Surface Model ◽

Matching Methods ◽

Sensing Applications ◽

Rational Polynomial ◽

Stereo Imagery ◽

Global Matching ◽

Commercial Purpose ◽

Matching Strategy

Large-scale Digital Surface Models (DSM) are very useful for many geoscience and urban applications. Recently developed dense image matching methods have popularized the use of image-based very high resolution DSM. Many commercial/public tools that implement matching methods are available for perspective images, but there are rare handy tools for satellite stereo images. In this paper, a software package, RPC (rational polynomial coefficient) stereo processor (RSP), is introduced for this purpose. RSP implements a full pipeline of DSM and orthophoto generation based on RPC modelled satellite imagery (level 1+), including level 2 rectification, geo-referencing, point cloud generation, pan-sharpen, DSM resampling and ortho-rectification. A modified hierarchical semi-global matching method is used as the current matching strategy. Due to its high memory efficiency and optimized implementation, RSP can be used in normal PC to produce large format DSM and orthophotos. This tool was developed for internal use, and may be acquired by researchers for academic and non-commercial purpose to promote the 3D remote sensing applications.

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