This paper studies a type of image priors that are constructed implicitly through the alternating direction method of multiplier (ADMM) algorithm, called the algorithm-induced prior. Different from classical image priors which are defined before running the reconstruction algorithm, algorithm-induced priors are defined by the denoising procedure used to replace one of the two modules in the ADM...

Abstract. Regularized minimization problems with nonconvex, nonsmooth, perhaps nonLipschitz penalty functions have attracted considerable attention in recent years, owing to their wide applications in image restoration, signal reconstruction and variable selection. In this paper, we derive affine-scaled second order necessary and sufficient conditions for local minimizers of such minimization p...

In 10] a theoretical framework for locally-adaptive smoothing of multi-dimensional data was presented. Based on this framework we introduce a hardware ef-cient architecture suitable for mixed-mode VLSI implementation. Substantial shortcomings of analogue implementations are overcome by connecting all cells in a circular structure: i) innuence of process parameter deviation ii) limited number of...

The Nonlocal Data and Smoothness (NDS) filtering framework for greyvalue images has been recently proposed by Mrázek et al. This model for image denoising unifies M-smoothing and bilateral filtering, and several well-known nonlinear filters from the literature become particular cases. In this article we extend this model to so-called matrix fields. These data appear, for example, in diffusion t...

a bottom up procedure for extracting repetitive structures in speech sounds has been developed on the basis of a temporally stable representation of periodic sounds (tandeM) and adaptive spectral smoothing (straiGht). the proposed method evaluates local periodic structures in the frequency domain to detect repetition in the time domain. a group of dedicated periodicity detectors are combined to...

In visual cortex information is processed along a cascade of neural mechanisms that pool activations from the surround with spatially increasing receptive fields. Watching a scenery of multiple moving objects leads to object boundaries on the retina defined by discontinuities in feature domains such as luminance or velocities. Spatial integration across the boundaries mixes distinct sources of ...

We present a regularized mixed norm multichannel image restoration algorithm. The problem of multichannel restoration using both withinand between-channel deterministic information is considered. For each channel a functional that combines the least mean squares (LMS), the least mean fourth (LMF), and a smoothing functional is proposed. We introduce a mixed norm parameter that controls the rela...

A novel nonlinear PDE based image denoising and restoration approach is provided in this article. The proposed anisotropic diffusion based technique is derived from the influential Perona-Malik nonlinear diffusion scheme, representing an enhanced version of that scheme. Our model is based on new versions of the edge-stopping function and the conductance parameter. The proposed PDE-based filteri...

An applicable method for generating mixed meshes around simple and medium complex configurations is presented. Core part of the mesh generation strategy is a smooth meshing of the boundary layer region by structured hexahedrons and prisms applying smoothing based on solving face-weighted Laplacian equations. A preconditioning of the point set for triangulation by shear and edge-weighted average...

Image magnification is a common problem in imaging applications, requiring interpolation to “read between the pixels”. Although many magnification/interpolation algorithms have been proposed in the literature, all methods must suffer to some degree the effects of imperfect reconstruction—false high-frequency content introduced by the underlying original sampling. Most often, these effects manif...