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Wavelet-Based Image Registration Techniques: A Study of Performance


Nagham E. Mekky, F. E.-Z. Abou-Chadi, S. Kishk


Vol. 11  No. 2  pp. 188-196


This paper presents a comparative study of performance for four wavelet-based multiresolution image registration techniques. The proposed algorithms are implemented and applied to dental panoramic X-ray images and magnetic resonance (MR) images of the brain. Cross-correlation based registration, mutual-information (MI) based hierarchical registration, scale invariant feature transform (SIFT) based registration, and hybrid registration approach using MI and SIFT operator combined with wavelet-based hierarchical pyramid, have been utilized. A comparison between proposed techniques with the corresponding techniques in the spatial domain is achieved. The quality of the registration process was measured using the following criteria: normalized cross-correlation coefficient (NCCC) and percentage relative root mean square error (PRRMSE). The application of the selected techniques to dental panoramic X-ray images and brain MR images has shown that wavelet-based hierarchical approach combining MI, SIFT, and RANdom Sample And Consensus (RANSAC) algorithm gives the best results and can be used efficiently for registration of two types of images.


Dentistry, hybrid approach, magnetic resonance (MR), mutual information, wavelet pyramid