Geometric Camera Calibration of BiLSAT Small Satellite Preliminary Results

Date

2006-02-14

Author

Friedrich, Jurgen
Leloğlu, Uğur Murat
Tunalı, Erol

Metadata

Show full item record

Item Usage Stats

177
views

0
downloads

The interior geometric calibration of the multi-spectral camera of BiLSAT satellite is aimed using three sets of images from Ankara. Each set contains four different images for channels Red, Green, Blue (RGB), and Near Infra Red (NIR) in which well-defined target points were identified and their image coordinates measured. The target points’ UTM coordinates were extracted from aerial photos or topographic maps and collected from field using hand-held GPS receiver. A least square parameter estimation was then applied to fit the image coordinates to the UTM coordinates and heights from the SRTM 90 m elevation model, thereby computing best estimates for the camera position and orientation as well as all the required geometric camera calibration parameters. These parameters were then analyzed and compared to each other. The obtained results show that the focal length f has a value of about f = 179 mm. Further, the principal point coordinates and radial lens distortions have a maximum of about ten pixels.

URI

https://hdl.handle.net/11511/82012
https://www.isprs.org/proceedings/XXXVI/1-W41/makaleler/Friedrich_BILSAT_geom.pdf

Collections

Graduate School of Natural and Applied Sciences, Conference / Seminar

Suggestions

OpenMETU
Core

Preliminary results of the alignment and Hartmann tests of the AZT-22 telescope Aslan, Z; Bikmaev, IF; Vitrichenko, EA; Gumerov, RI; Dembo, LA; Kamus, SF; Keskin, V; Kiziloglu, U; Pavlinsky, MN; Panteleev, LN; Sakhibullin, NA; Selam, SO; Sunyaev, RA; Khamitov, I; Yaskovich, AL (2001-06-01) The AZT-22 telescope installed in Turkey (Antalia) was aligned and tested on stars by the Hartmann method. The rms normal deviation of an equivalent optical system is 0.040 +/- 0.016 mum. The circle of confusion is 0.40 +/- 0.04 arcsec in diameter at a 50% energy level. (C) 2001 MAIK "Nauka/Interperiodica".
DEM generation and accuracy assessment from stereo ASTER imagery Ok, AO; Turker, M (2005-06-11) In this study, Digital Elevation Models (DEMs) were generated from ASTER stereo images for a study area enclosing the city of Ankara and covering an area of 3600 km(2). Majority of the area was covered by large scale orthophotos, which were used as the main source to collect the Ground Control Points (GCPs). For those areas that were not covered by the orthophotos the GCPs were collected through a differential GPS. The bundle adjustment process and the generation of DEMs were carried out using PCI Geomatica...
Hypothesis based detection of building with rectilinear projection in satellite images using shade and color information Güdücü, Volkan; Halıcı, Uğur (2010-12-01) A new hypothesis based method for detecting rectilinear buildings, that have ground projection made of combination of rectangles, in satellite images is proposed. While the hypotheses are established using the lines detected in the satellite images they are verified by using shadow and color segmentation information. The proposed method is implemented in MATLAB and tested in satellite images of different urban areas. The experimental results obtained are encouraging. ©2010 IEEE.
Differential Sensitivity Analysis for the Orthorectification of Small Satellite Images Bettemir, Oe. H. (2009-06-13) By using differential sensitivity analysis, horizontal and vertical accuracy of orthorectification of monoscopic images taken by small satellites without using Ground Control Points (GCP) is predicted. The analysis is performed by differentiating the colinearity equation of orthorectification procedure with respect to the satellite's interior and exterior parameters, and elevation obtained from digital elevation model (DEM). Square of the differential equations with respect to parameters are multiplied with...
Automatic building detection from high resolution satellite images Koc, D; Turker, M (2005-06-11) An approach was developed to update the buildings of existing vector database from high resolution satellite images using image classification, Digital Elevation Models (DEM) and object extraction techniques. First, the satellite image is classified using the Maximum Likelihood Classifier (MLC). The classified output provides the shapes and the approximate locations of the buildings. Next, a normalized Digital Surface Model (nDSM) is generated by subtracting the Digital Terrain Model (DTM) from the Digital ...

Citation Formats

J. Friedrich, U. M. Leloğlu, and E. Tunalı, “Geometric Camera Calibration of BiLSAT Small Satellite Preliminary Results,” 2006, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/82012.