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Proceedings Paper

Pseudo-correlation: a fast, robust, absolute, gray-level image alignment algorithm
Author(s): Thomas J. Radcliffe; Rasika Rajapakshe; Shlomo Shalev
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Paper Abstract

A new image alignment algorithm--pseudo-correlation--has been developed based on the application of Monte Carlo techniques to the calculation of a cross-correlation integral for grey-scale images. It has many advantages over cross-correlation: it is at least a factor of ten faster than FFT-based cross-correlation, and requires eight times less memory. Its high speed allows for the search space of geometric transformations between images to include magnification and rotation as well as translations without the search time becoming too long. It allows noise to be taken into account, making calculation of a robust, absolute probability of good alignment possible. It is relatively insensitive to differences in quality between images. This paper describes the pseudo-correlation algorithm and presents the results of tests of the effects of contrast enhancement and noise on the algorithm's performance. These tests show that the algorithm is well-suited to the task of automated alignment of very low contrast images from video electronic portal imaging devices (VEPIDs).

Paper Details

Date Published: 14 September 1993
PDF: 12 pages
Proc. SPIE 1898, Medical Imaging 1993: Image Processing, (14 September 1993); doi: 10.1117/12.154498
Show Author Affiliations
Thomas J. Radcliffe, Manitoba Cancer Treatment and Research Foundation (Canada)
Rasika Rajapakshe, Manitoba Cancer Treatment and Research Foundation (Canada)
Shlomo Shalev, Manitoba Cancer Treatment and Research Foundation and Univ. of Manitoba (Canada)


Published in SPIE Proceedings Vol. 1898:
Medical Imaging 1993: Image Processing
Murray H. Loew, Editor(s)

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