We propose a novel image denoising strategy based on an enhanced sparse representation
in transform domain. The enhancement of the sparsity is achieved by grou** similar 2D …

The paper discusses the theory behind the dual-tree transform, shows how complex
wavelets with good properties can be designed, and illustrates a range of applications in …

In this paper, we consider denoising of image sequences that are corrupted by zero-mean
additive white Gaussian noise. Relative to single image denoising techniques, denoising of …

We introduce novel image regularization penalties to overcome the practical problems
associated with the classical total variation (TV) scheme. Motivated by novel …

This thoroughly updated new edition presents state of the art sparse and multiscale image
and signal processing. It covers linear multiscale geometric transforms, such as wavelet …

In 1992, Bamberger and Smith proposed the directional filter bank (DFB) for an efficient
directional decomposition of 2-D signals. Due to the nonseparable nature of the system …

In this paper, we discuss about applications of different methods for decomposing a signal
over elementary waveforms chosen in a family called a dictionary (atomic representations) …

In this paper we present a new patch-based empirical Bayesian video denoising algorithm.
The method builds a Bayesian model for each group of similar space-time patches. These …

Standard-setting, groundbreaking, authoritative, comprehensive—these often overused
words perfectly describe The Circuits and Filters Handbook, Third Edition. This standard …

This paper introduces a novel recognition framework for human actions using hybrid
features. The hybrid features consist of spatio-temporal and local static features extracted …