Image Quality Measure Based On A Human Visual System Model

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Abstract
A preliminary image quality measure that takes into account two major sensitivities of the human visual system (HVS) is described. The sensitivities considered are background illumination level and spatial frequency sensitivities. Given a digitized monochrome image, the algorithm produces, among some other figures of merit, a plot of the information content (IC) versus the resolution in units of pixels. The IC is defined here as the sum of the weighted spectral components at an arbitrary specified resolution. The HVS normalization is done by first intensity remapping the image by a monotonically increasing function representing the background illumination level sensitivity, followed by a spectral filtering to compensate for the spatial frequency sensitivity. The developed quality measure is conveniently parameterized and interactive. It allows experimentation with numerous parameters of the HVS model to determine the optimum set for which the highest correlation with subjective evaluations can be achieved. The preliminary results are promising.

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