Title :
On the accuracy of approximations in the error analysis of registration systems
Author_Institution :
Saskatchewan Univ., Saskatoon, Sask., Canada
fDate :
11/1/1991 12:00:00 AM
Abstract :
The similarity functions used to register images are often approximated for the purposes of statistical analysis. An extension of a theorem for one-dimensional signals is presented that can assess the effects of approximations used in the statistical analysis of a registration system. The extended theorem facilitates the selection of an approximation that is sure to yield a pessimistic, or, if so preferred, an optimistic, variance of registration error. This method can be applied to a broad class of similarity functions that includes cross-correlation-based and linear-filter-based similarity functions.
Keywords :
approximation theory; correlation methods; error analysis; filtering and prediction theory; picture processing; statistical analysis; approximation; cross correlation; error analysis; extended theorem; image registration; linear filter; one-dimensional signals; registration systems; similarity functions; statistical analysis; variance of registration error; Autocorrelation; Equations; Error analysis; Filters; Fourier transforms; Nonlinear distortion; Polynomials; Statistical analysis;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
