Maximum Likelihood Image Registration With Subpixel Accuracy

Michael S Mort; M. D. Srinath

doi:10.1117/12.948429

16 December 1988 Maximum Likelihood Image Registration With Subpixel Accuracy

Michael S Mort, M. D. Srinath

Proceedings Volume 0974, Applications of Digital Image Processing XI; (1988) https://doi.org/10.1117/12.948429
Event: 32nd Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1988, San Diego, CA, United States

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.

Citation Download Citation

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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