Technical Program

Paper Detail

Paper:	SA-PM-PS1.5
Session:	Image Registration
Time:	Saturday, April 8, 13:30 - 14:50
Presentation:	Poster
Title:	Continuous Image Representations Avoid the Histogram Binning Problem in Mutual Information Based Image Registration
Authors:	Ajit Rajwade; University of Florida
	Arunava Banerjee; University of Florida
	Anand Rangarajan; University of Florida
Abstract:	Mutual information (MI) based image-registration methods that use histograms are known to suffer from the so-called binning problem, caused by the absence of a principled technique for choosing the “optimal” number of bins to calculate the joint or marginal distributions. In this paper, we show that foregoing the notion of an image as a set of discrete pixel locations, and adopting a continuous representation is the solution to this problem. A new technique to calculate joint image histograms is proposed, which makes use of such a continuous representation. We report results on affine registration of a pair of 2D medical images under high noise, and demonstrate the smoothness of various information-theoretic distance measures such as joint entropy orMI w.r.t. the transformation, when our proposed technique (referred to as the “robust histogram”) is adopted to compute the required probability distributions.

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