Description of Local Singularities for Image Registration

Recently, it has been shown that gradient-based methods are the most powerful approaches for describing the local content of digital images in the neighborhood of salient points. In practice, salient points are always located on image singularities whatever the detector used. In this paper, we show that a more efficient mathematical notion can be used to describe singularities: the Holder exponent. We propose here to conjointly use the Holder exponents and the direction of minimal regularity of the bidimensional signal singularities to compute a signature describing precisely a region of interest centered on an interest point. Holder exponents are estimated thanks to the foveal wavelets theory and the resulting descriptor is shown to be more efficient than classical SIFT and PCA-SIFT descriptors in the case of an image registration application