The performance of image registration algorithms for IR images depends on different system parameters such as SNR, gain, offset, image variance etc. in a very complex fashion. A statistical approach has been adopted to predict the performance of image registration algorithms , classical Correlation and Mean Absolute Difference algorithms, in terms of probability of correct registration as a function of different system parameters. Considering the complexity of the problem, some simplifying assumptions have been made regarding the random nature of different images as well as criteria function values which may not be strictly true for real environments. This analysis helps in understanding the sensitivity of different algorithms to different system parameters. This in turn helps to compare the performance of different registration algorithms in differe nt environments. A scheme for choosing adaptive threshold to meet constraints as probability of false hit and probability of miss, has also been proposed

Date Published: 1 October 1993
PDF: 12 pages
Proc. SPIE 1950, Acquisition, Tracking, and Pointing VII, (1 October 1993); doi: 10.1117/12.156904

Published in SPIE Proceedings Vol. 1950:
Acquisition, Tracking, and Pointing VII
Michael K. Masten; Larry A. Stockum, Editor(s)