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This noise gets present amid acquisition, transmission, and storage processes.
This fractal-based denoising algorithm can be applied in the pixel and the wavelet domains of the noisy image using standard fractal and fractal-wavelet schemes, respectively.
Furthermore, the cycle spinning idea was implemented in order to enhance the quality of the fractally denoised estimates.
In particular, three new image denoising methods are proposed: context-based wavelet thresholding, predictive fractal image denoising and fractal-wavelet image denoising.
The proposed context-based thresholding strategy adopts localized hard and soft thresholding operators which take in consideration the content of an immediate neighborhood of a wavelet coefficient before thresholding it.
The need for image enhancement and restoration is encountered in many practical applications.