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Title: An efficient exact algorithm for the ''least squares'' image registration problems

Abstract

Image registration involves estimating how one set of n-dimensional points is rotated, scaled, and translates into a second set of n- dimensional points. In practice, n is usually 2 or 3. We give an exact algorithm to solve the ''least-squares'' formulation of the two-dimensional registration problem. The algorithm, which is based on parametric linear programming, can be viewed as a refinement of the O(k/sup 3/) approximation method proposed by Zikan and Silberburg. The approach can be extended to handle registration of images of different cardinalities. 13 refs., 1 fig.

Authors:
Publication Date:
Research Org.:
Stanford Univ., CA (USA). Systems Optimization Lab.
OSTI Identifier:
6125034
Report Number(s):
SOL-89-5
ON: DE89013116
DOE Contract Number:  
FG03-87ER25028
Resource Type:
Technical Report
Resource Relation:
Other Information: Portions of this document are illegible in microfiche products
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; DATA; TRANSFORMATIONS; ANALYTICAL SOLUTION; ALGORITHMS; LEAST SQUARE FIT; LINEAR PROGRAMMING; TWO-DIMENSIONAL CALCULATIONS; INFORMATION; MATHEMATICAL LOGIC; MAXIMUM-LIKELIHOOD FIT; NUMERICAL SOLUTION; PROGRAMMING; 990230* - Mathematics & Mathematical Models- (1987-1989)

Citation Formats

Zikan, K. An efficient exact algorithm for the ''least squares'' image registration problems. United States: N. p., 1989. Web.
Zikan, K. An efficient exact algorithm for the ''least squares'' image registration problems. United States.
Zikan, K. Mon . "An efficient exact algorithm for the ''least squares'' image registration problems". United States. doi:.
@article{osti_6125034,
title = {An efficient exact algorithm for the ''least squares'' image registration problems},
author = {Zikan, K.},
abstractNote = {Image registration involves estimating how one set of n-dimensional points is rotated, scaled, and translates into a second set of n- dimensional points. In practice, n is usually 2 or 3. We give an exact algorithm to solve the ''least-squares'' formulation of the two-dimensional registration problem. The algorithm, which is based on parametric linear programming, can be viewed as a refinement of the O(k/sup 3/) approximation method proposed by Zikan and Silberburg. The approach can be extended to handle registration of images of different cardinalities. 13 refs., 1 fig.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon May 01 00:00:00 EDT 1989},
month = {Mon May 01 00:00:00 EDT 1989}
}

Technical Report:
Other availability
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