Generalizing a closed-form correlation model of oriented bandpass natural images

Building natural scene statistic models is a potentially transformative development for a wide variety of visual applications, ranging from the design of faithful image and video quality models to the development of perceptually optimized image enhancing techniques. Most predominant statistical models of natural images only characterize the univariate distributions of divisively normalized bandpass image responses. Previous efforts towards modeling bandpass natural responses have not focused on finding closed-form quantative models of bivariate natural statistics. Towards filling this gap, Su et al. [1] recently modeled spatially adjacent bandpass image responses over multiple scales; however, they did not consider the effects of spatial distance between the bandpass samples. Here we build on Su et al.'s model and extend their closed-form correlation model to non-adjacent distant bandpass image responses over multiple spatial orientations and scales.

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