DocumentCode
1035924
Title
A maximum likelihood approach for image registration using control point and intensity
Author
Li, Winston ; Leung, Henry
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Calgary, Alta., Canada
Volume
13
Issue
8
fYear
2004
Firstpage
1115
Lastpage
1127
Abstract
Registration of multidate or multisensor images is an essential process in many image processing applications including remote sensing, medical image analysis, and computer vision. Control point (CP) and intensity are the two basic features used separately for image registration in the literature. In this paper, an exact maximum likelihood (EML) registration method, which combines both CP and intensity, is proposed for image alignment. The EML registration method maximizes the likelihood function based on CP and intensity to estimate the registration parameters, including affine transformation and CP coordinates. The explicit formulas of the Cramer-Rao bound (CRB) are also derived for the proposed EML and conventional image registration algorithms. The performances of these image registration techniques are evaluated with the CRBs.
Keywords
computer vision; image registration; maximum likelihood estimation; sensor fusion; Cramer-Rao bound; affine transformation; computer vision; control point; image alignment; image processing application; image registration; maximum likelihood approach; medical image analysis; multisensor images; remote sensing; Application software; Biomedical imaging; Computer vision; Image analysis; Image processing; Image registration; Maximum likelihood estimation; Parameter estimation; Performance evaluation; Remote sensing; Algorithms; Image Enhancement; Image Interpretation, Computer-Assisted; Likelihood Functions; Models, Statistical; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2004.828435
Filename
1315700
Link To Document