The paper proposes a new wavelet-based Bayesian approach to image deconvolution, under the space-invariant blur and additive white Gaussian noise assumptions. Image deconvolution ...
This paper presents an efficient compression-oriented segmentation algorithm for computer-generated document images. In this algorithm, a document image is represented in a block-...
Jensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM algorithm, Bayesian estimation ...
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
Minhua Chen, Jorge Silva, John William Paisley, Ch...
In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly spa...