• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.774-778
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• 1996

Developed in this research is a surface modeling kernel for various CAD/CAM applications. Its internal surface representations are rational parametric polynomials, which are generalizations of nonrational Bezier, Ferguson, Coons and NURBS surface, and are very fast in evaluation. The kernel is designed under the OOP concepts and coded in C++ on PCs. The present implementation of the kernel supports surface construction methods, such as point data interpolation, skinning, sweeping and blending. It also has NURBS conversion routines and offers the IGES and ZES format for geometric information exchange. It includes some geometric processing routines, such as surface/surface intersection, curve/surface intersection, curve projection and so forth. We are continuing to work with the kernel and eventually develop a B-Rep based solid modeler.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.21-30
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• 2012

When two bands have different look angle in a space-borne camera system, the registration between two bands is required. The registration cannot be modeled with constant parameters because of dynamic of platform and parallax effect. The parallax effect is caused by terrain relief, hence it causes local distortion between two bands. Therefore, the terrain relief correction in order to reduce the parallax effect is required for better registration result, especially for high resolution image data. Such terrain relief correction also can be applied to image data acquired from multiple detectors with different look angle within a band, which is a one of commonly used configuration for a wider swath in space-borne camera system, in order to reduce the distortion between detectors. The RFM is a popular abstract model in remote sensing field, which gives us the relationship between the image plane and geodetic coordinate system. Therefore, we propose a terrain relief correction method based on the RFM. The experiment showed very promising result.