Automated bias-compensation of rational polynomial coefficients of high resolution satellite imagery based on topographic maps

Oh, Jaehong; Lee, Changno

doi:10.1016/j.isprsjprs.2014.02.009

Cited by 42 publications

(18 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In addition to the transformation function, the final orthoimage accuracy heavily depends on the precision of automatically extracted GCPs. Some automatic solutions for erroneous GCP removal (e.g., [12]) rely only on the data snooping method [13], which is not the optimal method, as it tends to fail when data with large errors and many gross errors are involved in the adjustment [14]. In these cases, more robust methods must be used.…”

mentioning

confidence: 99%

Automatic Orthorectification of High-Resolution Optical Satellite Images Using Vector Roads

Marsetič

Oštir

Fras

2015

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

This paper presents a completely automatic processing chain for orthorectification of optical pushbroom sensors. The procedure is robust and works without manual intervention from raw satellite image to orthoimage. It is modularly divided in four main steps: metadata extraction, automatic ground control point (GCP) extraction, geometric modeling, and orthorectification. The GCP extraction step uses georeferenced vector roads as a reference and produces a file with a list of points and their accuracy estimation. The physical geometric model is based on collinearity equations and works with sensor-corrected (level 1) optical satellite images. It models the sensor position and attitude with second-order piecewise polynomials depending on the acquisition time. The exterior orientation parameters are estimated in a least squares adjustment, employing random sample consensus and robust estimation algorithms for the removal of erroneous points and fine-tuning of the results. The images are finally orthorectified using a digital elevation model and positioned in a national coordinate system. The usability of the method is presented by testing three RapidEye images of regions with different terrain configurations. Several tests were carried out to verify the efficiency of the procedure and to make it more robust. Using the geometric model, subpixel accuracy on independent check points was achieved, and positional accuracy of orthoimages was around one pixel. The proposed procedure is general and can be easily adapted to various sensors.

show abstract

mentioning

confidence: 99%

Automatic Orthorectification of High-Resolution Optical Satellite Images Using Vector Roads

Marsetič

Oštir

Fras

2015

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Previous studies have shown that the bias-compensation method has slightly better accuracy than the polynomial model [8]. In the case of KOMPSAT, many studies have been carried out to improve the position accuracy using the bias-compensation method [11,19,20].…”

Section: Data Processingmentioning

confidence: 99%

Orthorectification of KOMPSAT Optical Images Using Various Ground Reference Data and Accuracy Assessment

Lee

Kim

2017

Journal of Sensors

View full text Add to dashboard Cite

Along with the appearance of high resolution satellite images, image correction using Rational Polynomial Coefficients (RPCs) has become common. Location accuracy of Korea Multipurpose Satellite (KOMPSAT) standard images is still not adequate, so, in order to leverage the KOMPSAT images for applications such as mapping and change detection, it is necessary to orthorectify the images. In this study, using updated RPCs, we performed orthorectification of KOMPSAT-2, KOMPSAT-3, and KOMPSAT-3A images using various data. Through this study, we discovered that the orthorectification result using precise Ground Control Points (GCPs) and Digital Elevation Model (DEM) is the best, but it was found that the correction results through image matching are also excellent. In particular, it was confirmed that orthoimages with a planimetric accuracy around 3 m (Root Mean Square Error (RMSE)) can be generated by using well-known matching algorithms with open data such as OpenStreetMap (OSM) and Shuttle Radar Topography Mission (SRTM) DEM, which can be acquired by anyone. Although the accuracy was low in some mountainous terrain, it was confirmed that it could be used for generating KOMPSAT orthoimages using open data. This paper describes the results for orthorectifying high resolution KOMPSAT optical images using various reference data.

show abstract

“…-of a stereo or a triplet pair are said to guarantee accuracy of plus or minus 10pix (CE90)(depending on the satellite employed), corresponding to up to 12m in the ground space (Oh and Lee, 2015). The absolute geo-location misalignment is due to limitations of the sensor's direct spatial positioning, primarily the attitude, the position and velocity (Fraser and Hanley, 2005).…”

Section: Refining the Rpc-based Sensor Orientationmentioning

confidence: 99%

Refined Satellite Image Orientation in the Free Open-Source Photogrammetric Tools Apero/Micmac

Rupnik¹,

Deseilligny²,

Delorme³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:This publication presents the RPC-based bundle adjustment implemented in the freeware open-source photogrammetric tool Apero/MicMac. The bundle adjustment model is based on some polynomial correction functions, enriched with a physical constraint that introduces the notion of a global sensor rotation into the model. The devised algorithms are evaluated against two datasets consisting of two stereo and a triplet pair of the Pleiades images. Two sets of correction functions and a number of GCPs configurations are examined. The obtained geo-referencing accuracy falls below the size of 1GSD.

show abstract

Automated bias-compensation of rational polynomial coefficients of high resolution satellite imagery based on topographic maps

Cited by 42 publications

References 6 publications

Automatic Orthorectification of High-Resolution Optical Satellite Images Using Vector Roads

Automatic Orthorectification of High-Resolution Optical Satellite Images Using Vector Roads

Orthorectification of KOMPSAT Optical Images Using Various Ground Reference Data and Accuracy Assessment

Refined Satellite Image Orientation in the Free Open-Source Photogrammetric Tools Apero/Micmac

Contact Info

Product

Resources

About