A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Time-frequency analysis: theory and applications
Time-frequency analysis: theory and applications
Geometric shock-capturing eno schemes for subpixel interpolation, computation and curve evolution
Graphical Models and Image Processing
Random Data: Analysis and Measurement Procedures
Random Data: Analysis and Measurement Procedures
Journal of Computational Physics
High resolution conjugate filters for the simulation of flows
Journal of Computational Physics
SIAM Journal on Scientific Computing
Numerical methods for the generalized Zakharov system
Journal of Computational Physics
DSC time-domain solution of Maxwell's equations
Journal of Computational Physics
Polynomial Fitting for Edge Detection in Irregularly Sampled Signals and Images
SIAM Journal on Numerical Analysis
Local spectral time splitting method for first- and second-order partial differential equations
Journal of Computational Physics
An EMD-based recognition method for Chinese fonts and styles
Pattern Recognition Letters
Matched interface and boundary (MIB) method for elliptic problems with sharp-edged interfaces
Journal of Computational Physics
Discontinuity detection in multivariate space for stochastic simulations
Journal of Computational Physics
Markov Random Field Modeling in Image Analysis
Markov Random Field Modeling in Image Analysis
Development of EMD-based denoising methods inspired by wavelet thresholding
IEEE Transactions on Signal Processing
Image change detection algorithms: a systematic survey
IEEE Transactions on Image Processing
Robust Image Watermarking Based on Multiband Wavelets and Empirical Mode Decomposition
IEEE Transactions on Image Processing
Mode Decomposition Evolution Equations
Journal of Scientific Computing
Selective extraction of entangled textures via adaptive PDE transform
Journal of Biomedical Imaging - Special issue on Mathematical Methods for Images and Surfaces 2011
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The synthesizing information, achieving understanding, and deriving insight from increasingly massive, time-varying, noisy and possibly conflicting data sets are some of most challenging tasks in the present information age. Traditional technologies, such as Fourier transform and wavelet multi-resolution analysis, are inadequate to handle all of the above-mentioned tasks. The empirical model decomposition (EMD) has emerged as a new powerful tool for resolving many challenging problems in data processing and analysis. Recently, an iterative filtering decomposition (IFD) has been introduced to address the stability and efficiency problems of the EMD. Another data analysis technique is the local spectral evolution kernel (LSEK), which provides a near prefect low pass filter with desirable time-frequency localizations. The present work utilizes the LSEK to further stabilize the IFD, and offers an efficient, flexible and robust scheme for information extraction, complexity reduction, and signal and image understanding. The performance of the present LSEK based IFD is intensively validated over a wide range of data processing tasks, including mode decomposition, analysis of time-varying data, information extraction from nonlinear dynamic systems, etc. The utility, robustness and usefulness of the proposed LESK based IFD are demonstrated via a large number of applications, such as the analysis of stock market data, the decomposition of ocean wave magnitudes, the understanding of physiologic signals and information recovery from noisy images. The performance of the proposed method is compared with that of existing methods in the literature. Our results indicate that the LSEK based IFD improves both the efficiency and the stability of conventional EMD algorithms.