Frequency and spatial pooling of visual differences for still image quality assessment

Objective image quality assessment techniques are currently based on the properties of the human visual system (HVS) essentially using early vision model. This type of approach allows to Set the differences between original and distorted images in a perceptually space,so the outputs of the early vision model are perceptual distortion maps. In order to get one mark for the overall distortion, spatial pooling and frequency pooling in case of spatial frequency decomposition should be applied on these maps. In this paper, we present various methods to do this pooling. In order to represent the distorted image in a perceptual space, we use a multi-channel early vision model including an amplitude nonlinearity, a CSF, a subband decomposition and a masking function. For the pooling, Minkowski summation with various exponents is first tested as it is the most common pooling in literature. The second type of pooling proposed achieves a summation of all the degradations weighted by a function of the probability of their occurrence. Finally we propose a summation taking into account some higher perceptual factors in order to point out the region of interest used to weight the errors. The results are compared measuring the correlation between the distortion marks and the MOS.