While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
Abstract— In this paper, we describe a two-step varianceadaptive method for image denoising based on a statistical model of the coefficients of balanced multiwavelet transform. ...
Abstract--This paper presents a new wavelet-based image denoising method, which extends a recently emerged "geometrical" Bayesian framework. The new method combines three...
Aleksandra Pizurica, Wilfried Philips, Ignace Lema...
Image restoration is a keen problem of low level vision. In this paper, we propose a novel - assumption-free on the noise model - technique based on random walks for image enhancem...
In our recent work, a class of parametric transforms, including family of Haar-like transforms, was introduced and studied in application to image compression. Parametric Haar-lik...