Nonlinear diffusion filtering for peak-preserving smoothing of a spectrum signal

被引:22
|
作者
Li, Yuanlu [1 ,2 ]
Ding, Yaqing [1 ]
Li, Tiao [1 ,2 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Informat & Control, B DAT, Nanjing 210044, Jiangsu, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Nanjing 210044, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Spectra; Nonlinear diffusion; Peak-preserving smoothing; Regularization method; Wavelet method; Savitzky-Golay method; CONTINUOUS WAVELET TRANSFORM; IMAGE NOISE REMOVAL; ANISOTROPIC DIFFUSION; DERIVATIVE SPECTROMETRY; RESOLUTION ENHANCEMENT; POLYNOMIAL FILTER; INFRARED-SPECTRA; EDGE-DETECTION; DIFFERENTIATION; QUANTIFICATION;
D O I
10.1016/j.chemolab.2016.06.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
How to reduce the noise while preserving the peak is a challenging task in analytical techniques. In this paper, the nonlinear diffusion was proposed as a general method to accomplish peak-preserving smoothing. The implement of the nonlinear diffusion is simple. Taking the noisy signal as the initial condition of a nonlinear diffusion equation, the solution is a smoothed signal, and signal becomes increasingly smooth as iteration number increases. Details of the nonlinear diffusion filtering and its implementation were given clearly. Some simulated signals and an NMR spectrum has been used to verify the proposed method and compare the performance of other methods such as regularization method, Savitzky-Golay method and wavelet method. Results indicated that the nonlinear diffusion is an excellent smoothing method, it can reduce the noise while preserve the peak shape. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:157 / 165
页数:9
相关论文
共 50 条
  • [1] EDGE-PRESERVING AND PEAK-PRESERVING SMOOTHING
    HALL, P
    TITTERINGTON, DM
    TECHNOMETRICS, 1992, 34 (04) : 429 - 440
  • [2] Time fractional super-diffusion model and its application in peak-preserving smoothing
    Li, Yuanlu
    Jiang, Min
    Liu, Fawang
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2018, 175 : 13 - 19
  • [3] Smoothing impulsive noise using nonlinear diffusion filtering
    Demirkaya, O
    COMPUTER VISION AND MATHEMATICAL METHODS IN MEDICAL AND BIOMEDICAL IMAGE ANALYSIS, 2004, 3117 : 111 - 122
  • [4] ON THE JOINT NONLINEAR FILTERING-SMOOTHING OF DIFFUSION-PROCESSES
    ZEITOUNI, O
    BOBROVSKY, BZ
    SYSTEMS & CONTROL LETTERS, 1986, 7 (04) : 317 - 321
  • [5] ISREA: An Efficient Peak-Preserving Baseline Correction Algorithm for Raman Spectra
    Xu, Yunnan
    Du, Pang
    Senger, Ryan
    Robertson, John
    Pirkle, James L.
    APPLIED SPECTROSCOPY, 2021, 75 (01) : 34 - 45
  • [6] Peak-aware guided filtering for spectrum signal denoising
    Liu, Donghong
    He, Chuanjiang
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2022, 222
  • [7] A Visual Analytics Approach for Peak-Preserving Prediction of Large Seasonal Time Series
    Hao, M. C.
    Janetzko, H.
    Mittelstaedt, S.
    Hill, W.
    Dayal, U.
    Keim, D. A.
    Marwah, M.
    Sharma, R. K.
    COMPUTER GRAPHICS FORUM, 2011, 30 (03) : 691 - 700
  • [8] Feature-Preserving Smoothing of Diffusion Weighted Images Using Nonstationarity Adaptive Filtering
    Zhang, Yan-Li
    Liu, Wan-Yu
    Magnin, Isabelle E.
    Zhu, Yue-Min
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2013, 60 (06) : 1693 - 1701
  • [9] A common framework for nonlinear diffusion, adaptive smoothing, bilateral filtering and mean shift
    Barash, D
    Comaniciu, D
    IMAGE AND VISION COMPUTING, 2004, 22 (01) : 73 - 81