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Kamalabadi, Farzad Bonham, Melody I. 2011-01-21T22:43:11Z 2011-01-21T22:43:11Z 2013-01-22T11:00:24Z 2011-01-21T22:43:11Z 2010-12 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. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2010-12-07T13:43:33Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Bonham_Melody.pdf: 1458676 bytes, checksum: f3f0c93647391cdeac31971244f0ca0e (MD5) Made available in DSpace on 2011-01-21T22:43:11Z (GMT). No. of bitstreams: 2 Bonham_Melody.pdf: 1458676 bytes, checksum: f3f0c93647391cdeac31971244f0ca0e (MD5) license.txt: 4061 bytes, checksum: 9b790013eb0a4e3e17d84ab62a058288 (MD5) Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by William Ingram (wingram2@illinois.edu) on 2011-01-21T22:47:51Z Item is restricted until 2013-01-21T22:47:37Z Item reinstated by Sarah Shreeves (sshreeve@illinois.edu) on 2013-01-22T11:00:24Z Item was in collections: University of Illinois Dissertations and Theses (ID: 204) Dissertations and Theses - Electrical and Computer Engineering (ID: 446) No. of bitstreams: 3 Bonham_Melody.pdf: 1458676 bytes, checksum: f3f0c93647391cdeac31971244f0ca0e (MD5) license.txt: 4061 bytes, checksum: 9b790013eb0a4e3e17d84ab62a058288 (MD5) Bonham_Melody.pdf.txt: 78142 bytes, checksum: edfed41d1011d684f71497be3c1fd1f4 (MD5) Item released from any restrictions by Sarah Shreeves (sshreeve@illinois.edu) on 2013-01-22T11:00:24Z http://hdl.handle.net/2142/18501 en Copyright 2010 Melody I. Bonham wavelet video multichannel denoise A near-optimal wavelet-based estimation technique for video sequences Electrical & Computer Eng 1933 Electrical & Computer Engr 1200 University of Illinois at Urbana-Champaign Thesis M.S. MS:Electr & Computer Eng-UIUC 10KS1200MS