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Flame Temperature Field Measurement Using Improved Generalized Cross Validation Method
Aizu-Wakamatsu City, Fukushima, Japan October 16-October 19
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIT.2007.507th IEEE International Conference on ...
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Yinghui Zhou, Dezhong Zheng, "Flame Temperature Field Measurement Using Improved Generalized Cross Validation Method," Computer and Information Technology, International Conference on, pp. 562-566, 7th IEEE International Conference on Computer and Information Technology (CIT 2007), 2007.
 
 
BibTex
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@article{ 10.1109/CIT.2007.50,
author = {Yinghui Zhou and Dezhong Zheng},
title = {Flame Temperature Field Measurement Using Improved Generalized Cross Validation Method},
journal ={Computer and Information Technology, International Conference on},
volume = {0},
year = {2007},
isbn = {0-7695-2983-6},
pages = {562-566},
doi = {http://doi.ieeecomputersociety.org/10.1109/CIT.2007.50},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer and Information Technology, International Conference on
TI - Flame Temperature Field Measurement Using Improved Generalized Cross Validation Method
SN - 0-7695-2983-6
SP562
EP566
A1 - Yinghui Zhou,
A1 - Dezhong Zheng,
PY - 2007
VL - 0
JA - Computer and Information Technology, International Conference on
ER -
 
Yinghui Zhou, Yanshan University, Qinhuangdao 066004 China
Dezhong Zheng, Yanshan University, Qinhuangdao 066004 China
The image quality is a crucial factor for calculating flame temperature field based on the color CCD method. However, much unknown noise in flame images would prevent from obtaining the temperature with accuracy. To eliminate noise, the wavelet denoising with soft-threshold is considered to be effective. An important parameter for this procedure is threshold. For flame images containing much unknown noise, the paper presents using improved Generalized Cross Validation law to get optimal threshold (GCV- threshold). This procedure does not require prior knowledge of noise level and is proved to be asymptotically optimal. For comparing denoised effect, an artificial noisy image is processed by different thresholds. The results show the GCV threshold is superior to others. Furthermore, the method is applied into the industrial flame image which indicates the accuracy of the temperature measurement has been improved.
Citation:
Yinghui Zhou, Dezhong Zheng, "Flame Temperature Field Measurement Using Improved Generalized Cross Validation Method," cit, pp.562-566, 7th IEEE International Conference on Computer and Information Technology (CIT 2007), 2007
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