Smoothness Prior Approach for Spectral Smoothing and Baseline Correction

Smoothness prior approach for spectral smoothing is investigated using Fourier frequency filter analysis.We show that the regularization parameter in penalized least squares could continuously control the bandwidth of low-pass filter.Besides,due to its property of interpolating the missing values automatically and smoothly,a spectral baseline correction algorithm based on the approach is proposed.This algorithm generally comprises spectral peak detection and baseline estimation.First,the spectral peak regions are detected and identified according to the second derivatives.Then,generalized smoothness prior approach combining identification information could estimate the baseline in peak regions.Results with both the simulated and real spectra show accurate baseline-corrected signals with this method.

Denoising of hyperspectral imagery by cubic smoothing spline in the wavelet domain

The acquired hyperspectral images （HSIs） are inherently attected by noise wlm Dano-varylng level, which cannot be removed easily by current approaches. In this study, a new denoising method is proposed for removing such kind of noise by smoothing spectral signals in the transformed multi- scale domain. Specifically, the proposed method includes three procedures： 1 ） applying a discrete wavelet transform （DWT） to each band; 2） performing cubic spline smoothing on each noisy coeffi- cient vector along the spectral axis; 3 ） reconstructing each band by an inverse DWT. In order to adapt to the band-varying noise statistics of HSIs, the noise covariance is estimated to control the smoothing degree at different spectra｜ positions. Generalized cross validation （GCV） is employed to choose the smoothing parameter during the optimization. The experimental results on simulated and real HSIs demonstrate that the proposed method can be well adapted to band-varying noise statistics of noisy HSIs and also can well preserve the spectral and spatial features.

The influence of smoothing by spectral dispersion on the beam characteristics in the near field

The influences of SSD on the beam characteristics in the near held are investigated. Results snow that it the SSD parameters are increased, the laser intensity modulation increases while fluence modulation decreases, which is attributed to the temporal and spatial variation of the SSD pulse phase. The variations of intensity and fluence modulations with the SSD parameters are given. The simulation results are presented along with a method for choosing appropriate SSD parameters according to the variations and the requirements of applications.

Investigation of stimulated rotational Raman scattering of the high-power broadband laser with applied angular dispersion

Smoothing by spectral dispersion （SSD） leads to considerable improvement on laser-irradiation uniformity in far field for fusion lasers. Phase modulation in time and spectral angular dispersion （SAD） across the beam introduced by SSD will affect the stimulated rotational Raman scattering （SRRS） gain in the near field. This paper focuses on the influence of SAD on SRRS gain under different laser conditions. Results show that the SAD will aggravate the generation of SRRS when the laser initial additional phase is constant. On the contrary, the SAD can reduce the SRRS gain if appropriate SSD parameters are adopted when the laser initial additional phase is variable. SSD has a certain application prospect in SRRS suppression.