Title :
A registration and matching method for remote sensing images
Author :
Ionescu, Dan ; AbdelSayed, Sherif ; Goodenough, David
Author_Institution :
Ottawa Univ., Ont., Canada
Abstract :
The analysis of a remote sensing image usually requires the comparison of the analyzed image with another image taken from the same spot. This paper describes a general-purpose, representation independent method for registering and matching remote sensing images. The method is based on the iterative closest point (ICP) algorithm. The algorithm requires a procedure to find the closest point on a geometric entity to a given point to measure the required deformation. A dynamic programming method is used for finding the best approximation of the deformation above. The corresponding points are then mapped into each other. A hypothesis propagation and verification method finds the features that match in the two images. An example from the Ottawa area illustrates the procedure
Keywords :
dynamic programming; image segmentation; image sequences; iterative methods; remote sensing; Ottawa area; deformation; dynamic programming method; hypothesis propagation method; image analysis; image segmentation; iterative closest point algorithm; matching method; registration method; remote sensing images; verification method; Dynamic programming; Image analysis; Image processing; Image sensors; Iterative algorithms; Iterative closest point algorithm; Iterative methods; Laser radar; Remote sensing; Shape;
Conference_Titel :
Electrical and Computer Engineering, 1993. Canadian Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2416-1
DOI :
10.1109/CCECE.1993.332395