scholarly journals QUASI-EPIPOLAR RESAMPLING OF HIGH RESOLUTION SATELLITE STEREO IMAGERY FOR SEMI GLOBAL MATCHING

2015 ◽  
Vol XL-1-W5 ◽  
pp. 707-712 ◽  
Author(s):  
N. Tatar ◽  
M. Saadatseresht ◽  
H. Arefi ◽  
A. Hadavand
Keyword(s):  
Stereo Matching ◽  
Stereo Pair ◽  
Matching Algorithm ◽  
Automatic Feature Extraction ◽  
Polynomial Coefficients ◽  
Sensor Model ◽  
Rational Polynomial ◽  
Straight Line ◽  
Stereo Imagery ◽  
Global Matching

Semi-global matching is a well-known stereo matching algorithm in photogrammetric and computer vision society. Epipolar images are supposed as input of this algorithm. Epipolar geometry of linear array scanners is not a straight line as in case of frame camera. Traditional epipolar resampling algorithms demands for rational polynomial coefficients (RPCs), physical sensor model or ground control points. In this paper we propose a new solution for epipolar resampling method which works without the need for these information. In proposed method, automatic feature extraction algorithms are employed to generate corresponding features for registering stereo pairs. Also original images are divided into small tiles. In this way by omitting the need for extra information, the speed of matching algorithm increased and the need for high temporal memory decreased. Our experiments on GeoEye-1 stereo pair captured over Qom city in Iran demonstrates that the epipolar images are generated with sub-pixel accuracy.

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

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

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.

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

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

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.

Evaluation of the RPC Model for Ziyuan-3 Three-Line Array Imagery

2017 ◽  
Author(s):  
Zhonghua Hong ◽  
Shengyuan Xu ◽  
Yun Zhang ◽  
Yanling Han ◽  
Yongjiu Feng
Keyword(s):  
Imaging System ◽  
Three Dimensional ◽  
Generic Model ◽  
Axis Direction ◽  
Polynomial Coefficients ◽  
Sensor Model ◽  
Rational Polynomial ◽  
Line Array ◽  
Physical Sensor ◽  
Sensor Models

Ziyuan-3 (ZY-3) satellite is the first civilian stereo mapping satellite in China and was designed to achieve the 1: 50000 scale mapping for land and ocean. Rigorous sensor model (RSM) is required to build the relationship between the three-dimensional (3D) object space and two-dimensional (2D) image space of ZY-3 satellite imagery. However, each satellite sensor has its own imaging system with different physical sensor models, which increase the difficulty of geometric integration of multi-source images with different sensor models. Therefore, it is critical to generate generic model especially rational polynomial coefficients (RPCs) of optical imagery. Recently, relatively a few researches have been conducted on RPCs generation to ZY-3 satellite. This paper proposes an approach to evaluate the performance of RPCs generation from RSM of ZY-3 imagery. Three scenarios experiments with different terrain features (such as ocean, city and grassland) are designed and conducted to comprehensively evaluate the replacement accuracies of this approach and analyze the RPCs fitting error. All the experimental results demonstrate that the proposed method achieved encouraging accuracy of better than 1.946E-04 pixel in both x-axis direction and y-axis direction, it indicates that the RPCs is suitable for ZY-3 imagery and can be used as a replacement for the RSM of ZY-3 imagery.

Real time area-based stereo matching algorithm for multimedia video devices

2013 ◽  
Vol 21 (4) ◽  
Author(s):  
T. Hachaj ◽  
M. Ogiela
Keyword(s):  
Real Time ◽  
Stereo Matching ◽  
Global Memory ◽  
Stereo Pair ◽  
Processing Unit ◽  
Process Data ◽  
Matching Algorithm ◽  
Knowing That ◽  
Algorithm Configuration ◽  
Graphical Processing

AbstractIn this paper we investigate stereovision algorithms that are suitable for multimedia video devices. The main novel contribution of this article is detailed analysis of modern graphical processing unit (GPU)-based dense local stereovision matching algorithm for real time multimedia applications. We considered two GPU-based implementations and one CPU implementation (as the baseline). The results (in terms of frame per second, fps) were measured twenty times per algorithm configuration and, then averaged (the standard deviation was below 5%). The disparity range was [0,20], [0,40], [0,60], [0,80], [0,100] and [0,120]. We also have used three different matching window sizes (3×3, 5×5 and 7×7) and three stereo pair image resolutions 320×240, 640×480 and 1024×768. We developed our algorithm under assumption that it should process data with the same speed as it arrives from captures’ devices. Because most popular of the shelf video cameras (multimedia video devices) capture data with the frequency of 30Hz, this frequency was threshold to consider implementation of our algorithm to be “real time”. We have proved that our GPU algorithm that uses only global memory can be used successfully in that kind of tasks. It is very important because that kind of implementation is more hardware-independent than algorithms that operate on shared memory. Knowing that we might avoid the algorithms failure while moving the multimedia application between machines operating different hardware. From our knowledge this type of research has not been yet reported.

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

2016 ◽  
Vol III-1 ◽  
pp. 77-82 ◽  
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.

A Parallel Stereo Matching Algorithm Core for FPGA Modeled by DSP Builder

2014 ◽  
Vol 536-537 ◽  
pp. 67-76
Author(s):  
Xiang Zhang ◽  
Zhang Wei Chen
Keyword(s):  
Stereo Matching ◽  
Cost Calculation ◽  
Stereo Pair ◽  
Disparity Map ◽  
High Definition ◽  
Matching Algorithm ◽  
Census Transform ◽  
Cost Aggregation ◽  
Dsp Builder ◽  
Fpga Chip

This paper proposes a FPGA implementation to apply a stereo matching algorithm based on a kind of sparse census transform in a FPGA chip which can provide a high-definition dense disparity map in real-time. The parallel stereo matching algorithm core involves census transform, cost calculation and cost aggregation modules. The circuits of the algorithm core are modeled by the Matlab/Simulink-based tool box: DSP Builder. The system can process many different sizes of stereo pair images through a configuration interface. The maximum horizon resolution of stereo images is 2048.

scholarly journals ORTORECTIFICATION OF SPOT-4 DATA USING RATIONAL POLYNOMIAL COEFFICIENTS

2012 ◽  
Vol 9 (1) ◽  
Author(s):  
Danang Surya Candra
Keyword(s):  
Satellite Orbit ◽  
Parallel Projection ◽  
Mean Square ◽  
Approximation Model ◽  
Positioning Accuracy ◽  
Projection System ◽  
Polynomial Coefficients ◽  
Sensor Model ◽  
Rational Polynomial ◽  
Physical Sensor

Orthorectification  of  satellite  imagery  can  be  done  in  two  ways  i.e.,  rigorous sensor  model  and  the  approximation  model  of  the  satellite’s  orbit.  Dependence  on  physicalparameters,  to  make  rigorous  sensor  model  is  more  complicated  and  difficult  to  apply.  The approximation  model  can be either  Rational Polynomial Coefficients (RPC)  model  or  parallel projection  system.  RPC  is  a  mathematical  model  which  is  not  depends  on  the  sensor.  It  is used to improve the positioning accuracy when the parameter of the physical sensor model is  unknown.  This  study  assessed  orthorectification  of  SPOT-4  using  the  RPC  model  with  7 coefficients. Root Mean Square Error (RMSE) of GCPs obtained from the study  was less than 1  pixel.  RPC  did  not  depend  on  physical  and  satellite  orbit  parameters.  Thus  the  RPC  was simpler and easier to apply.

Satellite-Imagery Geometric Accuracy Improvement Based on Direct Correction of Dominant Coefficients

2020 ◽  
Vol 86 (4) ◽  
pp. 215-224
Author(s):  
Xinming Tang ◽  
Changru Liu ◽  
Ping Zhou ◽  
Ning Cao ◽  
FengXiang Li ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Satellite Images ◽  
Geometric Accuracy ◽  
Accuracy Improvement ◽  
First Order ◽  
Polynomial Coefficients ◽  
Sensor Model ◽  
Rational Polynomial ◽  
Refinement Method ◽  
Correlation Problem

An important and difficult point in the application of satellite imagery is refining the positioning model and improving the geometric accuracy. In this study, we focus on improvement in geometric accuracy and develop a new rational function model (<small>RFM</small>) refinement method. First, we derive the conversion relationship between the rigorous sensor model and the <small>RFM</small>, based on which we illustrate the approximate meaning of the zero-order and first-order terms of the rational polynomial coefficients (<small>RPCs</small>). Second, the correlation problem between <small>RPCs</small> and the influence of individual <small>RPCs</small> on geometric positioning accuracy are analyzed and verified. The dominant coefficients that determine geolocation are then identified. Finally, a new <small>RFM</small> refinement method based on direct correction of the dominant coefficients is proposed and validated. The experiments, conducted with <small>ZY3-02</small> satellite imagery, indicate that the proposed method can effectively improve the geometric accuracy of satellite images.

scholarly journals SOLVING THE RATIONAL POLYNOMIAL COEFFICIENTS BASED ON L CURVE

2018 ◽  
Vol XLII-3 ◽  
pp. 2511-2515 ◽  
Author(s):  
G. Zhou ◽  
X. Li ◽  
T. Yue ◽  
W. Huang ◽  
C. He ◽  
...  
Keyword(s):  
Optimal Parameter ◽  
Least Square ◽  
Normal Equation ◽  
High Approximation ◽  
Camera Model ◽  
Approximation Accuracy ◽  
First Order ◽  
Polynomial Coefficients ◽  
Sensor Model ◽  
Rational Polynomial

The rational polynomial coefficients (RPC) model is a generalized sensor model, which can achieve high approximation accuracy. And it is widely used in the field of photogrammetry and remote sensing. Least square method is usually used to determine the optimal parameter solution of the rational function model. However the distribution of control points is not uniform or the model is over-parameterized, which leads to the singularity of the coefficient matrix of the normal equation. So the normal equation becomes ill conditioned equation. The obtained solutions are extremely unstable and even wrong. The Tikhonov regularization can effectively improve and solve the ill conditioned equation. In this paper, we calculate pathological equations by regularization method, and determine the regularization parameters by L&amp;thinsp;curve. The results of the experiments on aerial format photos show that the accuracy of the first-order RPC with the equal denominators has the highest accuracy. The high order RPC model is not necessary in the processing of dealing with frame images, as the RPC model and the projective model are almost the same. The result shows that the first-order RPC model is basically consistent with the strict sensor model of photogrammetry. Orthorectification results both the firstorder RPC model and Camera Model (ERDAS9.2 platform) are similar to each other, and the maximum residuals of X and Y are 0.8174&amp;thinsp;feet and 0.9272&amp;thinsp;feet respectively. This result shows that RPC model can be used in the aerial photographic compensation replacement sensor model.

scholarly journals Evaluation of the RPC Model for Ziyuan-3 Three-line Array Imagery

2017 ◽  
Author(s):  
Zhonghua Hong ◽  
Shengyuan Xu ◽  
Yun Zhang ◽  
Yanling Han ◽  
Yongjiu Feng
Keyword(s):  
Imaging System ◽  
Three Dimensional ◽  
Generic Model ◽  
Polynomial Coefficients ◽  
Sensor Model ◽  
Rational Polynomial ◽  
Line Array ◽  
Physical Sensor ◽  
Sensor Models ◽  
The Relationship

Ziyuan-3 (ZY-3) satellite is the first civilian stereo mapping satellite in China and was designed to achieve the 1:50000 scale mapping for land and ocean. Rigorous sensor model (RSM) is required to build the relationship between the three-dimensional (3D) object space and two-dimensional (2D) image space of ZY-3 satellite imagery. However, each satellite sensor has its own imaging system with different physical sensor models, which increase the difficulty of geometric integration of multi-source images with different sensor models. Therefore, it is critical to generate generic model especially rational polynomial coefficients (RPCs) of optical imagery. Recently, relatively a few researches have been conducted on RPCs generation to ZY-3 satellite. This paper proposes an approach to generate the RPCs for ZY-3 imagery from RSM. Three scenarios experiments with different terrain features (such as ocean, city and grassland) are designed and conducted to comprehensively evaluate the replacement accuracies of this approach and analyze the RPCs fitting error. All the experimental results demonstrate that the RPCs is suitable for ZY-3 imagery and can be used as a replacement for the RSM of ZY-3 imagery.

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