Now showing items 1-10 of 14
A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
We propose, analyze and test an alternating minimization algorithm for recovering images from blurry and noisy observa- tions with total variation (TV) regularization. This algorithm arises from a new half-quadratic model ...
A Fixed-Point Continuation Method for L_1-Regularization with Application to Compressed Sensing
We consider solving minimization problems with L_1-regularization: min ||x||_1 + mu f(x) particularly for f(x) = (1/2)||Ax-b||M2, where A is m by n and m < n. Our goal is to construct efficient and robust algorithms for ...
The Total Variation Regularized L1 Model for Multiscale Decomposition
This paper studies the total variation regularization model with an L1 fidelity term (TV-L1) for decomposing an image into features of different scales. We first show that the images produced by this model can be formed ...
A Comparison of Three Total Variation Based Texture Extraction Models
This paper qualitatively compares three recently proposed models for signal/image texture extraction based on total variation minimization:the Meyer, Vese-Osher, and TV-L1 models. We formulate discrete versions of these ...
A Fast TVL1-L2 Minimization Algorithm for Signal Reconstruction from Partial Fourier Data
Recent compressive sensing results show that it is possible to accurately reconstruct certain compressible signals from relatively few linear measurements via solving nonsmooth convex optimization problems. In this paper, ...
A Fast Algorithm for Edge-Preserving Variational Multichannel Image Restoration
We generalize the alternating minimization algorithm recently proposed in  to effciently solve a general, edge-preserving, variational model for recovering multichannel images degraded by within- and cross-channel ...
A Curvilinear Search Method for p-Harmonic Flows on Spheres
The problem of finding p-harmonic flows arises in a wide range of applications including micromagnetics, liquid crystal theory, directional diffusion, and chromaticity denoising. In this paper, we propose an innovative ...
A Matlab Implementation of a Flat Norm Motivated Polygonal Edge Matching Method using a Decomposition of Boundary into Four 1-Dimensional Currents
We describe and provide code and examples for a polygonal edge matching method.
Alternating Direction Augmented Lagrangian Methods for Semidefinite Programming
We present an alternating direction method based on an augmented Lagrangian framework for solving semidefinite programming (SDP) problems in standard form. At each iteration, the algorithm, also known as a two-splitting ...
Copula Density Estimation by Total Variation Penalized Likelihood with Linear Equality Constraints
A copula density is the joint probability density function (PDF) of a random vector with uniform marginals. An approach to bivariate copula density estimation is introduced that is based on a maximum penalized likelihood ...