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• W2035683610 abstract "Most of the commonly used stationary filtering techniques, performed either in the spatial or frequency domains, fail to produce good results for noisy signals with fast varying non-stationary structures. The filtering results could be improved by using space/spatial-frequency based non-stationary filters. Hence, a robust approach to space/spatial-frequency analysis of two-dimensional noisy signals is proposed in this paper. It is based on the two-dimensional L-estimate forms of the short-time Fourier transform, the spectrogram and the S-method. The proposed space/spatial-frequency distributions are used to define the L-estimate space-varying filtering procedure. It is designed for denoising of 2D non-stationary signals affected by the strong impulsive or mixed heavy-tailed and Gaussian noise. The efficiency of the proposed procedure is tested on the examples with interferogram-like images, textures and satellite images." @default.
• W2035683610 created "2016-06-24" @default.
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• W2035683610 date "2014-03-01" @default.
• W2035683610 modified "2023-09-23" @default.
• W2035683610 title "L-statistics based space/spatial-frequency filtering of 2D signals in heavy tailed noise" @default.
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• W2035683610 doi "https://doi.org/10.1016/j.sigpro.2013.08.021" @default.
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