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 ...
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 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) ...
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 ...
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 ...
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 ...