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 ...
Multiscale Image Segmentation Using Joint Texture and Shape Analysis
We develop a general framework to simultaneously exploit texture and shape characterization in multiscale image segmentation. By posing multiscale segmentation as a model selection problem, we invoke the powerful framework ...
Adaptive Representation of JPEG 2000 Images Using Header-based Processing
To bridge the mismatch between the sizes of images and display devices, we present an efficient and automatic algorithm to create an adaptive image representation called SmartNail. Given a digital image and rectangular ...
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 ...
ForWaRD: Fourier-Wavelet Regularized Deconvolution for Ill-Conditioned Systems
We propose an efficient, hybrid <i>Fourier-Wavelet Regularized Deconvolution</i> (ForWaRD) algorithm that performs noise regularization via scalar shrinkage in both the Fourier and wavelet domains. The Fourier shrinkage ...
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 ...