Praveen Cyriac

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The Wilson-Cowan equations were originally proposed to describe the low-level dynamics of neural populations (Wilson&Cowan 1972). These equations have been extensively used in modelling the oscillations of cortical activity (Cowan et al. 2016). However, due to their low-level nature, very few works have attempted connections to higher level psychophysics(More)
Image sensors in digital cameras capture values which are proportional to light intensity and within a range of between 3-4 orders of magnitude. These values are typically passed through a non-linearity prior to quantisation to a range of around 2 orders of magnitude. The purpose of the non-linearity is to ensure that the quantisation rate is approximately(More)
Given any metric that compares images of different dynamic range, we propose a method to reduce their distance with respect to this metric. The key idea is to consider the metric as a non local operator. Then, we transform the problem of distance reduction into a non local variational problem. In this context, the low dynamic range image having the smallest(More)
Due to technical limitations, common display devices can only reproduce images having a low range of intensity values (dynamic range). As a consequence, the dynamic range of images encoding real world scenes, which is large, has to be compressed in order for them to be reproduced on a common display, and this technique is called tone mapping. Because there(More)
Linear-nonlinear transforms are interesting in vision science because they are key in modeling a number of perceptual experiences such as color, motion or spatial texture. Here we first show that a number of issues in vision may be addressed through an analytic expression of the Jacobian of these linear-nonlinear transforms. The particular model analyzed(More)
In vision science, cascades of Linear+Nonlinear transforms are very successful in modeling a number of perceptual experiences [1]. However, the conventional literature is usually too focused on only describing the forward input-output transform. Instead, in this work we present the mathematical details of such cascades beyond the forward transform, namely(More)