Geometric Assessment of Non-physical Models for Geometric Correction of High Resolution Pushbroom Satellite Image Based on Point and Line Control Feature

Document Type : علمی - پژوهشی

Authors

1 M.Sc. Student, Dep. of Photogrammetry and Remote Sensing, College of Geodesy and Geomatics, K.N. Toosi University of Technology

2 Prof., Dep. of Photogrammetry and Remote Sensing, College of Geodesy and Geomatics, K.N. Toosi University of Technology

3 Postdoctoral Fellow, C-CORE, Memorial University of Newfoundland, St. John’s, Canada

Abstract

Non-physical models have attracted the attention of experts in the field of photogrammetry and remote sensing due to the lack for need of ephemeris data at the time of imaging and not providing raw images by owners of these images. In this paper, a comprehensive research was performed on non-physical models including: 3D Affine Model, First Order Rational Function Model with unequal denominator, SDLT, DLT, Rational Function Model with equal denominator, with the emphasis on the effect of linear and point features as control information to geometrically correct the high spatial resolution images. In addition, a new form of Pushbroom-Projective function is introduced, as a new idea for geometric correction of satellite images. The satellite images used in this research are GeoEye-1 from Urmia and Ikonos from Hamedan. Based on the results obtained, in the case of GeoEye-1 satellite image, First Order Rational Function Model with unequal denominator when using point features as control and +XY term of Rational Function Model with equal denominator when applying linear features as control reached the highest accuracy of 0.75 pixel and 2.03 pixel respectively. In the case of Ikonos satellite image, the +XY term of Rational Function Model with equal denominator when using control point features and First Order Rational Function Model with unequal denominator when using linear control features reached the accuracy of 0.68 pixel and 1.5 pixel respectively at the best. It is worth mentioning that the remaining systematic errors in the case of using linear features as control are always more than those obtained using point control features.

Keywords

References

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