Statistica Sinica MINIMAX WAVELET SHRINKAGE A ROBUST INCORPORATION OF INFORMATION ABOUT ENERGY OF A SIGNAL IN DENOISING APPLICATIONS
نویسندگان
چکیده
In this paper we propose a method for wavelet ltering of noisy signals when prior information about the L energy of the signal of interest is available Assuming the independence model according to which the wavelet coe cients are treated individually we propose a level dependent shrinkage rule that turns out to be the minimax rule for a suitable class say of realistic priors on the wavelet coe cients The proposed methodology is particularly well suited for denoising tasks where signal to noise ratio is low and it is illustrated on a battery of standard test func tions Performance comparisons with some others methods existing in the literature are provided An example in atomic force microscopy AFM is also discussed
منابع مشابه
-Minimax Wavelet Shrinkage: A Robust Incorporation of Information about Energy of a Signal in Denoising Applications
In this paper we propose a method for waveletltering of noisy signals when prior information about the energy of the signal of interest is available. Assuming the independence model, according to which the wavelet coeÆcients are treated individually, we propose a level dependent shrinkage rule that turns out to be the -minimax rule for a suitable class of realistic priors on the wavelet coeÆcie...
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