_wavelet_threshold(image, wavelet, method=None, threshold=None, sigma=None, mode='soft', wavelet_levels=None)
Input data to be denoised. :None:None:`image` can be of any numeric type, but it is cast into an ndarray of floats for the computation of the denoised image.
The type of wavelet to perform. Can be any of the options pywt.wavelist outputs. For example, this may be any of {db1, db2,
db3, db4, haar}
.
Thresholding method to be used. The currently supported methods are "BayesShrink" and "VisuShrink" . If it is set to None, a user-specified threshold
must be supplied instead.
The thresholding value to apply during wavelet coefficient thresholding. The default value (None) uses the selected method
to estimate appropriate threshold(s) for noise removal.
The standard deviation of the noise. The noise is estimated when sigma is None (the default) by the method in .
An optional argument to choose the type of denoising performed. It noted that choosing soft thresholding given additive noise finds the best approximation of the original image.
The number of wavelet decomposition levels to use. The default is three less than the maximum number of possible decomposition levels (see Notes below).
Denoised image.
Perform wavelet thresholding.
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