A near-optimal wavelet-based estimation technique for video sequences
Bonham, Melody I.
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https://hdl.handle.net/2142/18501
Description
Title
A near-optimal wavelet-based estimation technique for video sequences
Author(s)
Bonham, Melody I.
Issue Date
2011-01-21T22:43:11Z
Director of Research (if dissertation) or Advisor (if thesis)
Kamalabadi, Farzad
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
wavelet
video
multichannel
denoise
Abstract
This thesis presents a method for estimation of a video signal given a data set with Poisson
noise. The cameras used in creating video sequences are often charge-coupled devices,
which produce data by way of a counting process, leading to noise with a Poisson
distribution. Because many applications using video require data with less noise, a method
of reducing the noise and estimating the original signal is desired. The method presented
in this thesis attempts to accomplish this goal without using a Wiener lter, which can
de-noise signals and is optimal in the mean-square error sense, but is hard to implement
because second-order statistics may be unknown and because of the inversion of a possibly
large matrix. Instead, an approximation of the Wiener lter is accomplished by rst
performing a one-dimensional discrete Fourier transform in order to decorrelate the video
sequence between each two-dimensional frame or across each channel, and then performing
a two-dimensional discrete wavelet transform on each of the resulting frames. Thresholding
is then implemented, and the inverse transform is applied in order to recover an estimate of
the original signal. It is shown that this scheme is e ective in improving signal-to-noise
ratio in synthetic video sequences and video captured by a camera.
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