Now showing items 1-6 of 6
Wavelet-based deconvolution for ill-Conditioned systems
This thesis proposes a new approach to wavelet-based image deconvolution that comprises Fourier-domain system inversion followed by wavelet-domain noise suppression. In contrast to other wavelet-based deconvolution approaches, ...
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 ...
Wavelet-based deconvolution for ill-conditioned systems
We propose a hybrid approach to wavelet-based deconvolution that comprises Fourier-domain system inversion followed by wavelet-domain noise suppression. In contrast to other wavelet-based deconvolution approaches, the ...
A Statistical Multiscale Framework for Poisson Inverse Problems
This paper describes a statistical modeling and analysis method for linear inverse problems involving Poisson data based on a novel multiscale framework. The framework itself is founded upon a multiscale analysis associated ...
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 ...
Toward an Improved Understanding of Network Traffic Dynamics
Since the discovery of long range dependence in Ethernet LAN traces there has been significant progress in developing appropriate mathematical and statistical techniques that provide a physical-based, networking-related ...