000063070 001__ 63070
000063070 005__ 20181203020019.0
000063070 0247_ $$2doi$$a10.1109/83.887976
000063070 02470 $$2DAR$$a2994
000063070 02470 $$2ISI$$a000165517200009
000063070 037__ $$aARTICLE
000063070 245__ $$aOptimization of Mutual Information for Multiresolution Image Registration
000063070 269__ $$a2000
000063070 260__ $$bIEEE$$c2000
000063070 336__ $$aJournal Articles
000063070 500__ $$a Erratum     p. 2085, second column, third line, the numeric value for S is incorrect. It should read S ≅ −0.811 instead of S ≅ −0.865.  
000063070 520__ $$9eng$$a We propose a new method for the intermodal registration of images using a criterion known as mutual information. Our main contribution is an optimizer that we specifically designed for this criterion. We show that this new optimizer is well adapted to a multiresolution approach because it typically converges in fewer criterion evaluations than other optimizers. We have built a multiresolution image pyramid, along with an interpolation process, an optimizer, and the criterion itself, around the unifying concept of spline-processing. This ensures coherence in the way we model data and yields good performance. We have tested our approach in a variety of experimental conditions and report excellent results. We claim an accuracy of about a hundredth of a pixel under ideal conditions. We are also robust since the accuracy is still about a tenth of a pixel under very noisy conditions. In addition, a blind evaluation of our results compares very favorably to the work of several other researchers. 
000063070 6531_ $$aInterpolation
000063070 700__ $$0240172$$aThévenaz, P.$$g115226
000063070 700__ $$0240182$$aUnser, M.$$g115227
000063070 773__ $$j9$$k12$$q2083–2099$$tIEEE Transactions on Image Processing
000063070 8564_ $$uhttp://bigwww.epfl.ch/publications/thevenaz0003.ps$$zURL
000063070 8564_ $$uhttp://bigwww.epfl.ch/publications/thevenaz0003.html$$zURL
000063070 8564_ $$s1255489$$uhttps://infoscience.epfl.ch/record/63070/files/thevenaz0003.pdf$$zn/a
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