TITLE:
Noise Reduction in White Light Lidar Signal Using a One-Dim and Two-Dim Daubechies Wavelet Shrinkage Method
AUTHORS:
Toshihiro Somekawa, Maria Cecilia D. Galvez, Masayuki Fujita, Edgar A. Vallar, Chihiro Yamanaka
KEYWORDS:
White Light Lidar; Multi-Wavelength; Wavelet; Daubechies
JOURNAL NAME:
Advances in Remote Sensing,
Vol.2 No.1,
March
25,
2013
ABSTRACT: A 1-D and 2-D Daubechies 5 (db5) discrete wavelet shrinkage methods using a 10 level decomposition was applied to white light lidar data particularly at 350 nm and 550 nm backscattered signal. At 350 nm, the backscattered signal is very weak as compared to 550 nm backscattered signal because of the spectral intensity distribution of the generated white light. The 1-D and 2-D wavelet shrinkage method gave a much better result as compared with the moving average method. However, the 2-D wavelet shrinkage method produced a much better denoised lidar signal compared with the 1-D wavelet shrinkage method. This is indicated by the 142% increase in correlation coefficient between the 2-D denoised lidar signal and the 800 nm original lidar signal as compared with only 12% increase in correlation coefficient for the 1-D denoised lidar signal. The 2-D wavelet shrinkage method also gave a much higher SNR value of 65.9 compared to 1-D which is 38.8.