Paper
16 December 1988 Maximum Likelihood Image Registration With Subpixel Accuracy
Michael S Mort, M. D. Srinath
Author Affiliations +
Abstract
The problem addressed in this paper is to estimate, with an error which is substantially less than the dimensions of a pixel, the unknown displacement d between two images of a common scene, given only the image data. Assuming a Gauss-Markov model for the scene, the joint probability density function of the two images is obtained and an implicit expression for the maximum likelihood estimate of the displacement is found as the maximum of a functional J(c1). The sensitivity of the algorithm to the model parameters has been determined by experiments on 32 real images. The experiments show that a mean absolute error of 1/20 of a pixel dimension is achievable for rms signal to rms noise ratios down to a value of 5.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael S Mort and M. D. Srinath "Maximum Likelihood Image Registration With Subpixel Accuracy", Proc. SPIE 0974, Applications of Digital Image Processing XI, (16 December 1988); https://doi.org/10.1117/12.948429
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CITATIONS
Cited by 17 scholarly publications and 3 patents.
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KEYWORDS
Signal to noise ratio

Image filtering

Image registration

Digital image processing

Error analysis

Digital imaging

Image processing

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