Now showing items 1-6 of 6
Multiscale Likelihood Analysis and Image Reconstruction
The nonparametric multiscale polynomial and platelet methods presented here are powerful new tools for signal and image denoising and reconstruction. Unlike traditional wavelet-based multiscale methods, these methods are ...
Image Restoration Using the EM Algorithm and Wavelet-Based Complexity Regularization
This paper introduces an <i>expectation-maximization</i> (EM) algorithm for image restoration (deconvolution) based on a penalized likelihood formulated in the wavelet domain. Regularization is achieved by promoting a ...
Platelets for Multiscale Analysis in Medical Imaging
This paper describes the development and use of multiscale, platelet-based image reconstruction algorithms in medical imaging. Such algorithms are effective because platelets approximate images in certain (piecewise) ...
Platelets for Multiscale Analysis in Photon-Limited Imaging
This paper proposes a new multiscale image decomposition based on platelets. Platelets are localized functions at various scales, locations, and orientations that produce piecewise linear image approximations. For smoothness ...
Platelets: A Multiscale Approach for Recovering Edges and Surfaces in Photon-Limited Medical Imaging
This paper proposes a new multiscale image decomposition based on platelets. Platelets are localized functions at various scales, locations, and orientations that produce piecewise linear image approximations. Platelets ...
Model-based Inverse Halftoning with Wavelet-Vaguelette Deconvolution
In this paper, we demonstrate based on the linear model of Kite that inverse halftoning is equivalent to the well-studied problem of deconvolution in the presence of colored noise. We propose the use of the simple and ...