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We propose a novel and efficient SAR image despeckling via Bayesian shrinkage based on nonsubsampled contourlet transform, which has been recently introduced. Despeckling by means of contourlet transform introduce many visual artifacts due to the Gibbs-like phenomena. Nonsubsampled contour let transform is a flexible multiscale, multidirection and shift-invariant image decomposition that can be efficiently...
In recent years, Brain-computer interface (BCI) based on electroencephalogram (EEG) is an active topic in brain function research. BCI provides a direct communication and control channel for sending messages and instructions from brain to external computers or other electronic devices. However, the EEG signals are very faint and often corrupted by noises such as power line noise, EMG, EOG etc.. EEG...
A novel and efficient improving PWF method of speckle reduction in polarimetric SAR image by fusion based on nonsubsampled contourlet transform is proposed. First, the three complex elements (HH, HV, and VV) of the polarimetric scattering matrix were decorrelated to form a new elements matrix. Then we show that the sub-band decompositions of the three elements using nonsubsampled contourlet transform,...
We propose a novel and efficient SAR image despeckling via bivariate shrinkage based on contourlet transform, which has been recently introduced. Contourlet transform is a flexible multi-scale, multi-direction and multi-resolution image decomposition that can be efficiently implemented via transform. A bivariate shrinkage with local variance estimation is applied to the decomposed contourlet coefficients...
The electroencephalogram (EEG) is widely used by physicians for interpretation and identification of physiological and pathological phenomena. However, the EEG signals are often corrupted by power line interferences noise and EMG induced noise. These artifacts strongly influence the utility of recorded EEGs and need to be removed for better clinical diagnosis. How to eliminate the effect of the noise...
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