Improvement of Threshold Function Based on Wavelet De-noising
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.
*Author to whom correspondence should be addressed.
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.
Keywords: Wavelet threshold, image de-noising, improved methods, threshold function