October 22, 2013
Comments Off on Modeling Natural Images Using Gated MRFs
Posted in: Final year projects
Abstract This paper describes a Markov Random Field for real-valued image modeling that has two sets of latent variables. One set is used to gate the interactions between all pairs of pixels, while the second set determines the mean intensities of each pixel. This is a powerful model with a conditional distribution over the input […]
October 22, 2013
Comments Off on Image Enhancement Using the Hypothesis Selection Filter: Theory and Application to JPEG Decoding
Posted in: Final year projects
Abstract We introduce the hypothesis selection filter (HSF) as a new approach for image quality enhancement. We assume that a set of filters has been selected a priori to improve the quality of a distorted image containing regions with different characteristics. At each pixel, HSF uses a locally computed feature vector to predict the relative […]