NDLI: Extracting subtle feature of target signal based on double tree complex wavelet transformation

Content Provider	IEEE Xplore Digital Library
Author	Liu Jihai Li Dongsheng Xu Jiren Cheng Jiasong Gao Huaihui
Copyright Year	2011
Description	Author affiliation: Department of information, Eletric engineering Institute of Hefei, Hefei, Anhui (Liu Jihai; Li Dongsheng; Xu Jiren; Cheng Jiasong; Gao Huaihui)
Abstract	Double tree after wavelet transform has good direction selectivity and invariant parallel movement. Based on analysing histogram of modulus sub-band corresponding to six high frequency sub-band after double tree wavelet decomposition, we put forwaord a new kind of subtle character, namely combination character of Lognormal distribution parameters and Gamma distribution parameter. Using the character to segment signal feature, and using edge smooth technology in the process of segmentation and using k-means clustering to realize unsupervised segmentation. Experiments show that the method of feature extraction is new, and edge accuracy of segmentation results and regional consistency has antinoise character, and it is a kind of effective subtle segmentation method.
Starting Page	1177
Ending Page	1180
File Size	1016874
Page Count	4
File Format	PDF
ISBN	9781612840871
e-ISBN	9781612840888
DOI	10.1109/EMEIT.2011.6023304
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gamma distribution Accuracy Wavelet domain Double tree wavelet transform Subtle features Feature extraction Wavelet analysis Discrete wavelet transforms Lognormal distribution
Content Type	Text
Resource Type	Article

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