Log-polar transformation (LPT) is widely used in image registration due to its scale and rotation
invariant properties. Through LPT, rotation and scale transformation can be made into translation displacement
in log-polar coordinates, and phase correlation technique can be used to get the displacement. In LPT based image
registration, constant samples in digitalization processing produce less precise and effective results. Thus, dynamic
log-polar transformation (DLPT) is used in this paper. DLPT is a method that generates several sample sets in
axes to produce several results and only the effective results are used to get the final results by using statistical
approach. Therefore, DLPT can get more precise and effective transformation results than the conventional LPT.
Mutual information (MI) is a similarity measure to align two images and has been used in image registration for
a long time. An optimal transform for image registration can be obtained by maximizing MI between the two
images. Image registration based on MI is robust in noisy, occlusion and illumination changing circumstance. In
this paper, we study image registration using MI and DLPT. Experiments with digitalizing images and with real
image datasets are performed, and the experimental results show that the combination of MI with DLPT is an
effective and precise method for image registration.
ZHANG Kui* (张葵), ZHANG Xiao-long (张晓龙), XU Xin (徐新), FU Xiao-wei (付晓薇)
. Mutual Information Optimization Based Dynamic Log-Polar Image Registration[J]. Journal of Shanghai Jiaotong University(Science), 2015
, 20(1)
: 61
-67
.
DOI: 10.1007/s12204-015-1589-8
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