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 ...
TEMPLAR: A Wavelet-Based Framework for Pattern Learning and Analysis
Despite the success of wavelet decompositions in other areas of statistical signal and image processing, current wavelet-based image models are inadequate for modeling patterns in images, due to the presence of unknown ...
WInHD: Wavelet-based Inverse Halftoning via Deconvolution
We propose the <i>Wavelet-based Inverse Halftoning via Deconvolution</i> (WInHD) algorithm to perform inverse halftoning of error-diffused halftones. WInHD is motivated by our realization that inverse halftoning can be ...
Multiscale Density Estimation
The nonparametric density estimation method proposed in this paper is computationally fast, capable of detecting density discontinuities and singularities at a very high resolution, spatially adaptive, and offers near ...
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 ...