2011 · 12 citations · 8 references
ComputingComputer ScienceComputer VisionDigital ImagingMachine VisionImage RegistrationPattern RecognitionPose EstimationShape AnalysisFeature MatchingHistogram AnalysisHistogram MatchingImage AlignmentImage MatchingMutual Information RegistrationRegistration AccuracySimilarity Criteria
This paper researches the mutual information matching algorithm for image registration. Firstly, feature points are extracted from images by Harris corner detector operator. Then, it uses mutual information as the similarity criteria for feature points' coarse matching. At last, it adapts random sample consensus algorithm (RANSAC) to filter the results of the coarse matching in order to eliminate errors and inconsistent with the camera motion matching point. We discuss the window size and the number of histogram bins which influence the result of registration. Large experimental results show that the method can make a satisfactory registration accuracy and stability.
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Martin A. Fischler, Robert C. Bolles · Communications of the ACM · 1981 · 25.5K citations · Full text
Evaluation of Interest Point Detectors
Cordelia Schmid, Roger Mohr, Christian Bauckhage · International Journal of Computer Vision · 2000 · 1.4K citations · Full text
Alignment by maximization of mutual information
Paul Viola, William M. Wells · 2002 · 1.1K citations · Full text