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- W2793785993 abstract "The wavelet thresholding technique as a multi-scale denoising technique has an outstanding performance in non-stationary signal processing. Currently, this technique was effectively used in noise reduction of Light detection and ranging (Lidar) echo signals. However, the traditional hard and soft thresholding functions lead to the oscillation and detail distortion, respectively, which limits denoising performance. Some revised thresholding functions proposed on the basis of the traditional functions are fixed, which can hardly ensure the optimal performance in different conditions. Therefore, we propose the generalized wavelet thresholding functions and provide the design principle. By adjusting the tuning parameters to compare the signal to noise ratio (SNR) of output in iteration, the optimal performance is finally reached. We apply the proposed functions to the on-site, experimental Lidar data, demonstrate the feasibility of our approach, and derive the optimal noise reduction of the Lidar echo signal, which effectively improves the range accuracy." @default.
- W2793785993 created "2018-03-29" @default.
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- W2793785993 date "2017-11-27" @default.
- W2793785993 modified "2023-09-24" @default.
- W2793785993 title "Generalized wavelet thresholding technique for optimal noise reduction of Lidar echo signals" @default.
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- W2793785993 doi "https://doi.org/10.1145/3163080.3163098" @default.
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