Translation, orentation, and scale estimation based on Laguerre-Gauss circular harmonic pyramids

This paper deals with the problem of accurate position, orientation and scale estimation (localization) of objects in images, in the context of the Laguerre-Gauss Transform (GLT) theory. The solution proposed here is based on the maximization of the Maximum Likelihood functional, expressed by means of the Laguerre-Gauss expansion of the object and of the observed image. The original computational complexity of the problem, which would imply maximization over a four dimensional parameter space, is drastically reduced taking advantage of properties of the GLT image representation system.