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Image Noise Removal in Nakagami Fading Channels via Bayesian Estimator
Kuala Lumpur, Malaysia January 17-January 19
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DELTA.2006.54Third IEEE International Workshop on ...
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Xu Huang, A.C. Madoc, Dharmendra Sharma, "Image Noise Removal in Nakagami Fading Channels via Bayesian Estimator," Electronic Design, Test and Applications, IEEE International Workshop on, pp. 31-34, Third IEEE International Workshop on Electronic Design, Test and Applications (DELTA'06), 2006.
 
 
BibTex
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@article{ 10.1109/DELTA.2006.54,
author = {Xu Huang and A.C. Madoc and Dharmendra Sharma},
title = {Image Noise Removal in Nakagami Fading Channels via Bayesian Estimator},
journal ={Electronic Design, Test and Applications, IEEE International Workshop on},
volume = {0},
year = {2006},
isbn = {0-7695-2500-8},
pages = {31-34},
doi = {http://doi.ieeecomputersociety.org/10.1109/DELTA.2006.54},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Electronic Design, Test and Applications, IEEE International Workshop on
TI - Image Noise Removal in Nakagami Fading Channels via Bayesian Estimator
SN - 0-7695-2500-8
SP31
EP34
A1 - Xu Huang,
A1 - A.C. Madoc,
A1 - Dharmendra Sharma,
PY - 2006
KW - digital image
KW - image noise removal
KW - Bayesian estimator
KW - wavelet
KW - wireless communications
KW - Nakagami m- fading channels.
VL - 0
JA - Electronic Design, Test and Applications, IEEE International Workshop on
ER -
 
Xu Huang, University of Canberra,Canberra, Australia
A.C. Madoc, University of Melbourne, VIC, Australia
Dharmendra Sharma, University of Canberra,Canberra, Australia
A maximum likelihood for Bayesian estimator based on ?-stable was discussed in our previous papers. It is in terms of closer to a realistic situation, and unlike previous methods used for Bayesian estimator, for the case discussed here it is not necessary to know the variance of the noise. The Bayesian estimator here is based on in a Nakagami fading channel. Our previous research results has been extended to that Bayesian estimator that we investigated is still working well for the image noise removal in Nakagami fading channels. As an example, an improved Bayesian estimator (soft and hard threshold methods), is illustrated in our discussion.
Index Terms:
digital image, image noise removal, Bayesian estimator, wavelet, wireless communications, Nakagami m- fading channels.
Citation:
Xu Huang, A.C. Madoc, Dharmendra Sharma, "Image Noise Removal in Nakagami Fading Channels via Bayesian Estimator," delta, pp.31-34, Third IEEE International Workshop on Electronic Design, Test and Applications (DELTA'06), 2006
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