1/

f

-Type noise

specially modeled by fractional Brownian motion (fBm) has attracted much attention in many fields.A multiscale Wiener filter based on biorthonormal wavelets and equipped with Wiener filter is proposed in this paper for signal restoration embedded in

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family of fractal signals.First

the signal with

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noise is transformed via the analysis filter bank into multiscale subsystems in time-scale domain based on biorthonormal wavelets.Some nostationary properties

e.g.self-similarity

long-term dependencies of fractal signals are attenuated in each subband by wavelet multiresolution decomposition so that the Wiener filter bank can be applied to estimate the multiscale input signals.Then the estimated multiscale input signals are synthesized to obtain

the estimated signal.Some simulation examples are given for testing the performance of the proposed algorithm.With this multiscale analysis/synthesis design via the technique of the wavelet filter bank

the multiscale Wiener filter can be applied to treat the signal restoration problem from nonstationary

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fractal noise.

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fractal noise was restrained effectively and the signal to noise is improved evidently.