Adaptive Thresholding Denoising Algorithm Based on Cross-Validation

摘要：

AbstractIn this paper, a novel wavelet-based adaptive thresholding de-noising algorithm is proposed. By using a modified twofold Cross-validation, a noise-corrupted signal is divided into two parts: one for estimating, the other one acts as a reference signal, and they make it possible to search for the optimal threshold using steepest gradient method. The numerical results indicate that the proposed optimal-threshold-based denoising algorithm outperforms the standard wavelet shrinkage methods, like Donohoˇs VisuShrink and SureShrink, in MSE sense. The proposed algorithm does not need any a priori information of the noise-distorted signal, and its convergence speed is high. It fits to real-time signal processing.

作者: Wenqing Huang Yuxing

作者单位: College of electrical and information engineering Hunan University Changsha, Hunan, China

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 276-279

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）