scholarly journals NUMERICAL EVALUATION AND APPLICATION-ORIENTED ANALYSIS FOR FORWARD AND INVERSE RATIONAL FUNCTION MODELS OF TERRAIN-INDEPENDENT CASE IN SATELLITE IMAGERY

2014 ◽  
Vol 40 (3) ◽  
pp. 99-109 ◽  
Author(s):  
Sorosh Jahandideh ◽  
Ali Azizi ◽  
Nasser Najibi
Keyword(s):  
Data Processing ◽  
Satellite Imagery ◽  
Control Points ◽  
Virtual Control ◽  
Polynomial Coefficients ◽  
Rational Polynomial ◽  
Aerospace Companies ◽  
Independent Case ◽  
Function Models ◽  
And Control

Terrain-independent Rational Polynomial Coefficients (RPCs) are considered as most important part of the optical satellite and aerial imagery data processing especially those ones with high resolution since the proposed RPCs by the aerospace companies have some limitations in particular for using directly by the geoscientists in environmental studies and other Earth observation applications. While the inverse RPCs have more advantageous rather than direct ones, in this study, a new approach is presented in order to provide the inverse RPCs from direct ones and also to satisfy satellite imagery products users. In order to do this, first a spatial 3D-cubic is going to be fitted to the study area approximately including necessary altimetry layers numbers. Next, a range of virtual control points are being created in those altimetry layers randomly and then these points are going to be shifted to the image space by means of given direct RPCs. Hence, the inverse RPCs computes from the direct ones by space resection technique. Finally, the ground coordinates for the corresponding points have derived from different space intersection methodologies, direct RPCs and also inverse ones. Moreover, comparative tests have been developed to assess the effects of different altimetry layers numbers and also the number of virtual control points on the quality of derived inverse RPCs. It is demonstrated here that the precision of derived RPCs are increasing as much as the number of altimetry layers and control points increase. The proposed methodology, computations, data processing and results evaluation are discussed in details.

scholarly journals AUTOMATIC REGISTRATION OF GF4 PMS: A HIGH RESOLUTION MULTI-SPECTRAL SENSOR ON BOARD A SATELLITE ON GEOSTATIONARY ORBIT

2018 ◽  
Vol XLII-3 ◽  
pp. 359-362
Author(s):  
M. Gao ◽  
J. Li
Keyword(s):  
Geometric Control ◽  
Reference Image ◽  
Control Points ◽  
Automatic Registration ◽  
Geometric Correction ◽  
Polynomial Coefficients ◽  
Rational Polynomial ◽  
Manual Selection ◽  
Base Band ◽  
Selection Of

Geometric correction is an important preprocessing process in the application of GF4 PMS image. The method of geometric correction that is based on the manual selection of geometric control points is time-consuming and laborious. The more common method, based on a reference image, is automatic image registration. This method involves several steps and parameters. For the multi-spectral sensor GF4 PMS, it is necessary for us to identify the best combination of parameters and steps. This study mainly focuses on the following issues: necessity of Rational Polynomial Coefficients (RPC) correction before automatic registration, base band in the automatic registration and configuration of GF4 PMS spatial resolution.

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.

Optimal selection of virtual control points with planar constraints for large‐scale block adjustment of satellite imagery

2020 ◽  
Vol 35 (172) ◽  
pp. 487-508
Author(s):  
Xiaohua Tong ◽  
Qing Fu ◽  
Shijie Liu ◽  
Hanyu Wang ◽  
Zhen Ye ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Large Scale ◽  
Optimal Selection ◽  
Control Points ◽  
Virtual Control ◽  
Selection Of

scholarly journals Positioning Accuracy Analysis and Application for Worldview-1 Stereo Imagery

2014 ◽  
Vol XL-4 ◽  
pp. 311-314
Author(s):  
Z. Xiao ◽  
B. Yang ◽  
H. Zhang
Keyword(s):  
Satellite Image ◽  
Systematic Errors ◽  
Control Points ◽  
Accuracy Analysis ◽  
Positioning Accuracy ◽  
Polynomial Coefficients ◽  
Rational Polynomial ◽  
Stereo Imagery

This article introduced the progress of processing the WorldView-1 satellite image by using the air triangulation method．And different adjustment models were used to improve the vendor provided RPC (Rational Polynomial Coefficients) accuracy. WorldVfew-1 images in Beijing are used to test the correction accuracy of these adjustment models．Results show that the systematic errors of RPC model can be eliminated using a small amount of control points. The planar RMSE can reach 1.6 pixels (0.9 meter)．

scholarly journals THE RATIONAL POLYNOMIAL COEFFICIENTS MODIFICATION USING DIGITAL ELEVATION MODELS

2015 ◽  
Vol XL-1-W5 ◽  
pp. 47-50 ◽  
Author(s):  
F. Alidoost ◽  
A. Azizi ◽  
H. Arefi
Keyword(s):  
Point Cloud ◽  
Digital Elevation Models ◽  
Ground Control ◽  
Control Points ◽  
Polynomial Coefficients ◽  
Ground Control Points ◽  
Rational Polynomial ◽  
Digital Elevation ◽  
Elevation Model ◽  
Parameters Calculation

The high-resolution satellite imageries (HRSI) are as primary dataset for different applications such as DEM generation, 3D city mapping, change detection, monitoring, and deformation detection. The geo-location information of HRSI are stored in metadata called Rational Polynomial Coefficients (RPCs). There are many methods to improve and modify the RPCs in order to have a precise mapping. In this paper, an automatic approach is presented for the RPC modification using global Digital Elevation Models. The main steps of this approach are: relative digital elevation model generation, shift parameters calculation, sparse point cloud generation and shift correction, and rational polynomial fitting. Using some ground control points, the accuracy of the proposed method is evaluated based on statistical descriptors in which the results show that the geo-location accuracy of HRSI can be improved without using Ground Control Points (GCPs).

scholarly journals KOMPSAT-3 Digital Elevation Model Correction Based on Point-to-Surface Matching

2019 ◽  
Vol 11 (20) ◽  
pp. 2340 ◽  
Author(s):  
Hyoseong Lee ◽  
Michael Hahn
Keyword(s):  
Satellite Images ◽  
Surface Matching ◽  
Control Points ◽  
Polynomial Coefficients ◽  
Ground Control Points ◽  
Rational Polynomial ◽  
Digital Elevation ◽  
High Resolution Satellite Images ◽  
Coordinate Measurements ◽  
Elevation Model

In order to generate digital elevation models (DEMs) from high-resolution satellite images, the vendor-provided rational polynomial coefficients (RPCs) are commonly used. This results in a level of accuracy that can be improved by using ground control points (GCPs). The integration of the GCPs into the processing chain is associated with additional effort, since it requires the provision of GCPs as well as the measurement of its image coordinates. In this paper, the authors avoid the measurement of GCP image coordinates and propose a point-to-surface matching method to correct the DEM produced from KOMPSAT-3 satellite images and the provided RPCs. For point-to-surface matching, an existing network of GCPs was used in South Korea, the so-called united control points and the triangulation control points. Practical testing was summarized with the proposed method in which the root mean square error with respect to the horizontal position and the height reduced from 20 m and 6 m to 3 m and 2 m, respectively. This demonstrates that neither image coordinate measurements nor additional GCP point acquisition, e.g., by GPS, are necessary to convert a DEM generated from KOMPSAT-3 images and vendor-provided RPCs into a highly accurate DEM by using existing GCPs and point-to-surface matching.

scholarly journals LARGE SCALE CITY MAPPING USING SATELLITE IMAGERY / KOSMINIŲ NUOTRAUKŲ IŠ GOOGLE EARTH, TAIKOMŲ MIESTAMS KARTOGRAFUOTI STAMBIUOJU MASTELIU, REKTIFIKAVIMAS / РЕКТИФИКАЦИЯ КОСМИЧЕСКИХ СНИМКОВ ИЗ GOOGLE EARTH ДЛЯ КРУПНОМАСШТАБНОГО КАРТОГРАФИРОВАНИЯ ГОРОДОВ

2012 ◽  
Vol 37 (4) ◽  
pp. 168-171 ◽  
Author(s):  
Birutė Ruzgienė ◽  
Qian Yi Xiang ◽  
Silvija Gečytė
Keyword(s):  
Satellite Imagery ◽  
Large Scale ◽  
Modern Technology ◽  
Google Earth ◽  
Aerial Images ◽  
Control Points ◽  
Image Rectification ◽  
Image Deformation ◽  
Map Construction ◽  
Short Period

The rectification of high resolution digital aerial images or satellite imagery employed for large scale city mapping is modern technology that needs well distributed and accurately defined control points. Digital satellite imagery, obtained using widely known software Google Earth, can be applied for accurate city map construction. The method of five control points is suggested for imagery rectification introducing the algorithm offered by Prof. Ruan Wei (tong ji University, Shanghai). Image rectification software created on the basis of the above suggested algorithm can correct image deformation with required accuracy, is reliable and keeps advantages in flexibility. Experimental research on testing the applied technology has been executed using GeoEye imagery with Google Earth builder over the city of Vilnius. Orthophoto maps at the scales of 1:1000 and 1:500 are generated referring to the methodology of five control points. Reference data and rectification results are checked comparing with those received from processing digital aerial images using a digital photogrammetry approach. The image rectification process applying the investigated method takes a short period of time (about 4-5 minutes) and uses only five control points. The accuracy of the created models satisfies requirements for large scale mapping. Santrauka Didelės skiriamosios gebos skaitmeninių nuotraukų ir kosminių nuotraukų rektifikavimas miestams kartografuoti stambiuoju masteliu yra nauja technologija. Tai atliekant būtini tikslūs ir aiškiai matomi kontroliniai taškai. Skaitmeninės kosminės nuotraukos, gautos taikant plačiai žinomą programinį paketą Google Earth, gali būti naudojamos miestams kartografuoti dideliu tikslumu. Siūloma nuotraukas rektifikuoti Penkių kontrolinių taskų metodu pagal prof. Ruan Wei (Tong Ji universitetas, Šanchajus) algoritmą. Moksliniam eksperimentui pasirinkta Vilniaus GeoEye nuotrauka iš Google Earth. 1:1000 ir 1:500 mastelio ortofotografiniai žemėlapiai sudaromi Penkių kontrolinių taškų metodu. Rektifikavimo duomenys lyginami su skaitmeninių nuotraukų apdorojimo rezultatais, gautais skaitmeninės fotogrametrijos metodu. Nuotraukų rektifikavimas Penkių kontrolinių taskų metodu atitinka kartografavimo stambiuoju masteliu reikalavimus, sumažėja laiko sąnaudos. Резюме Ректификация цифровых и космических снимков высокой резолюции для крупномасштабного картографирования является новой технологией, требующей точных и четких контрольных точек. Цифровые космические снимки, полученные с использованием широкоизвестного программного пакета Google Earth, могут применяться для точного картографирования городов. Для ректификации снимков предложен метод пяти контрольных точек с применением алгоритма проф. Ruan Wei (Университет Tong Ji, Шанхай). Для научного эксперимента использован снимок города Вильнюса GeoEye из Google Earth. Ортофотографические карты в масштабе 1:1000 и 1:500 генерируются с применением метода пяти контрольных точек. Полученные результаты и данные ректификации сравниваются с результатами цифровых снимков, полученных с применением метода цифровой фотограмметрии. Ректификация снимков с применением метода пяти контрольных точек уменьшает временные расходы и удовлетворяет требования, предъявляемые к крупномасштабному картографированию.

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