Digital image fusion and compression

Joint representations have experimented a significant height in signal processing during the last decades, to such an extent that there is no topic they have not been utilized for. Within a sea of joint representations existent in the literature, one of them concerns the present work: the log-Gabor multiresolution transform. Its significant mathematical properties (low spectral overlapping, high selectivity, shift-invariance, self-invertibility, complex-valued) and similarity to the cortical area V1 of the Visual Human System allow to extract salient features which traces new routes to face image processing tasks, in particular in the areas of image fusion and compression.

Autorentext

Received PhD in 2007 from ETSIT (Universidad Politécnica de Madrid, Spain). He currently works at Instituto de Óptica (CSIC) since 2001 and among his research elds are vision modeling, image and volumetric coding algorithms and time-frequency representations applied to pattern recognition, image fusion and compression.