Improvement of Threshold Function Based on Wavelet De-noising

Yi Lingzhi; Xiao Weihong; Yu Wenxin; Wang Genping

doi:10.9734/BJMCS/2016/29055

Research Article Open access CC BY 4.0

Improvement of Threshold Function Based on Wavelet De-noising

Yi Lingzhi, Xiao Weihong, Yu Wenxin, Wang Genping

Journal of Advances in Mathematics and Computer Science · pp. 1–9 · Published 27 Sep 2016

10.9734/BJMCS/2016/29055

Abstract

Hard threshold function is discontinuity in the threshold point, and soft threshold function have a constant error between the estimated coefficient of wavelet and the original coefficient of wavelet. To solve this problem, an improved threshold function is presented, which is continuous and high-order-differential in the threshold point. The experimental results show that the de-noising effect of this function is better than the soft threshold function, the hard threshold function and the modular square function.

Wavelet threshold image de-noising improved methods threshold function

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Yi Lingzhi, Xiao Weihong, Yu Wenxin, Wang Genping (2016). Improvement of Threshold Function Based on Wavelet De-noising. Journal of Advances in Mathematics and Computer Science , 1–9. https://doi.org/10.9734/BJMCS/2016/29055

Affiliations

Yi Lingzhi — Hunan Province Cooperative Innovation Center for Wind Power Equipment and Energy Conversion, College of Information Engineering, Xiangtan University, Hunan, Xiangtan, 411105, P.R. China.
Xiao Weihong — Hunan Province Cooperative Innovation Center for Wind Power Equipment and Energy Conversion, College of Information Engineering, Xiangtan University, Hunan, Xiangtan, 411105, P.R. China.
Yu Wenxin — Hunan University of Science and Technology, Hunan, Xiangtan, 411201, P.R. China.
Wang Genping — Shenzhen Polytechnic, Shenzhen, 518000, Guangdong, P.R. China.

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