Optics Express · 2012 · 60 citations · 32 references
EngineeringVision ScienceComputer VisionDigital ImagingMachine VisionDigital Image ProcessingDigital Signal ProcessingImage PreprocessingImage ProcessingMorphological OperationsSignal ProcessingBackground RemovalDiscrete Wavelet TransformEmpirical Mode DecompositionFourier TransformFringe AnalysisLocal ExtremaSiftingWavelet Transform
A modified bi-dimensional empirical mode decomposition (BEMD) method is proposed for sparsely decomposing a fringe pattern into two components, namely, a single intrinsic mode function (IMF) and a residue. The main idea of this method is a modified sifting process which employs morphological operations to detect ridges and troughs of the fringes, and uses weighted moving average algorithm to estimate envelopes of the IMF, replacing respective local extrema detection and envelope interpolation of conventional BEMDs. The background intensity of the fringe pattern is automatically removed by extracting the single IMF, thereby relieving the mode mixing problem of the BEMDs. A fast algorithm based on 2D convolution is also presented for reducing the calculation time to several seconds only. This approach is applied to process simulated and real fringe patterns, and the results obtained are compared with Fourier transform, discrete wavelet transform, and other EMD methods. The MATLAB code is downloadable at http://gr.xjtu.edu.cn/web/zhouxiang.
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Norden E. Huang, Steven Long, Man‐Li C. Wu et al. · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 1998 · 23.3K citations · Full text
Computing, Computational Engineering, Biomedical Signal Processing +16
A universal image quality index
Zhou Wang, Alan C. Bovik · IEEE Signal Processing Letters · 2002 · 5.7K citations