On the representation of image structures via scale space entropy conditions
Mario Ferraro, Giuseppe Boccignone, Terry Caelli · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1999
This paper deals with a novel way for representing and computing image features encapsulated within different regions of scale-space. Employing a thermodynamical model for scale-space generation, the method derives features as those corresponding to "entropy rich" image regions where, within a given range of spatial scales, the entropy gradient remains constant. Different types of image features, defining regions of different information content, are accordingly encoded by such regions within different bands of spatial scale.