Spectral Graph Wavelet Based Nonrigid Image Registration
Résumé
We propose a nonrigid registration method whose motion estimation is cast into a feature matching problem under the Log-Demons framework using Graph Wavelets. We investigate the Spectral Graph Wavelets (SGWs) to capture the shape feature of the images. The advantages of the Spectral Graph Wavelet (SGW) over the classical wavelet is that data representation on graphs is more adapted to data with complex structures. Our experiments on T1 brain images and endomicroscopic images show that this method outperforms the existing nonrigid image registration techniques (i.e. Log-Demons and Spectral Log-Demons) with improved similarity values.
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