Abstract
Methods of noisy image filtration using wavelet transforms with real and complex basis sets have been compared. It is shown that the use of a complex wavelet transform provides more effective filtration and admits automatic optimization of the filter parameters. Optimized choice of the threshold level during filtration based on a complex wavelet transform significantly decreases the error of image reconstruction as compared to that achieved with a standard method of discrete wavelet transform employing basis sets of the Daubechies wavelet family.
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