Flame image of pint-sized power plant's boiler denoising using wavelet-domain HMT models

Authors:
Chunguang Ji;Ru Zhang;Shitao Wen;Shiyong Li
Affiliations:
Harbin Institute of Technology, School of Computer Science and Technology, Harbin, P.R. China;Harbin Institute of Technology, School of Computer Science and Technology, Harbin, P.R. China;Harbin Institute of Technology, School of Computer Science and Technology, Harbin, P.R. China;Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, P.R. China
Venue:
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Year:
2005

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Abstract

Wavelet-domain hidden Markov Tree (HMT) was recently pro-posed and often applied to image processing. In this paper, HMT is app-lied to denoise the flame image of boiler and has gotten a good result. Having compared with other denoise methods such as wavelet, Wiener filter and median filter. HMT can get better denoise result and the content of flame image edges can be kept better. With the development of HMT research, it will be extended to the fields of signal processing, detection of edge and classification.