Open AccessIntrinsic bias in Fisher information calculations for multi-mode image registration
Author(s) -
David W. Tyler
Publication year - 2018
Publication title -
optics letters/optics index
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.524
H-Index - 272
eISSN - 1071-2763
pISSN - 0146-9592
DOI - 10.1364/ol.43.002292
Subject(s) - computer science , transformation (genetics) , artificial intelligence , image registration , image processing , computer vision , mode (computer interface) , optics , pattern recognition (psychology) , image (mathematics) , physics , biochemistry , chemistry , gene , operating system
To address the need for the analysis of image processing and optical requirements in multi-mode imaging systems, such as multi-spectral and polarimetric imagers, I have developed a Fisher information matrix to quantify errors in estimating the shift between images with non-transformational feature differences. If images of the same field have differences not attributable to a geometric transformation, as is common for images acquired using different spectral or polarization filters, uncertainty in estimating the parameters of the transformation will be increased by intrinsic bias, or bias inherent in the data itself, as opposed to bias originating in the estimation algorithm. The approach to shift-estimation error analysis described in this Letter accounts for intrinsic bias, has intuitively expected properties and, given planned system sensitivity and operating conditions, can be used with simulated multi-mode imagery to estimate image registration error and develop realistic requirements.