Rayleigh Lidar Signal Denoising Method Combined with WT, EEMD and LOWESS to Improve Retrieval Accuracy

A Signal Denoising Method for Full-waveform Lidar Data

The lack of noise reduction methods resistant to waveform distortion can hamper correct and accurate decomposition in the processing of full-waveform LiDAR data. This paper evaluates a time-domain method for smoothing and reducing the noise level in such data. The Savitzky-Golay (S-G) approach approximates and smooths data by taking advantage of fitting a polynomial of degree d, using local lea...

Atmospheric Lidar Noise Reduction Based on Ensemble Empirical Mode Decomposition

As an active remote sensing instrument, lidar provides a high spatial resolution vertical profile of aerosol optical properties. But the effective range and data reliability are often limited by various noises. Performing a proper denoising method will improve the quality of the signals obtained. The denoising method based on ensemble empirical mode decomposition (EEMD) is introduced, but the d...

A Method to Improve Accuracy and Precision

Background and Purpose High-resolution ultrasonographic imaging is a nonnvasive method that allows estimation of the thickness of the intima-media complex in human carotid arteries. The determination of intima-media thickness involves several steps, each of which may introduce an error that influences the reproducibility of the method. In the present study, apart from the general reproducibilit...

Analysis on wind retrieval methods for Rayleigh Doppler lidar

A Survey on the Performance Analysis of WT, PF, EMD & EEMD Methods used in ECG Signal Processing

A noiseless ECG identification technology is an emerging new biometric modality. Different techniques for de-noising of ECG signal are prevalent in recent literatures such as Particle Filter (PF), wavelet transforms (WT), Empirical Mode Decomposition (EMD) & Ensemble-EMD Method. In view of the fact that Analysis of ECG signals becomes difficult to inspect the cardiac activity in the presence of...