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.