We propose a new image and blur prior model, based on nonstationary autoregressive (AR) models, and use these to blindly deconvolve blurred photographic images, using the Gibbs sa...
We tackle the problem of object recognition using a Bayesian approach. A marked point process [1] is used as a prior model for the (unknown number of) objects. A sample is generat...
Stochastic device noise has become a significant challenge for high-precision analog/RF circuits, and it is particularly difficult to correctly include both white noise and flic...
The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Mont...
Jonathan M. R. Byrd, Stephen A. Jarvis, A. H. Bhal...
Patch based denoising methods, such as the NL-Means, have emerged recently as simple and efficient denoising methods. This paper provides a new insight on those methods by showing...