Minimum Noiseless Description Length (MNDL) Thresholding

Minimum Noiseless Description Length (MNDL) Thresholding

In this paper, a new thresholding approach for data denoising is presented. The approach is based minimum noiseless description length (MNDL), a new method for optimum sub-space selection in data representation. By using the observed noisy data, this information theoretic approach provides the optim...

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Bibliographische Detailangaben
Hauptverfasser: Fakhrzadeh, A., Beheshti, S.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Additive noise
Computational intelligence
Data engineering
Image reconstruction
Noise reduction
Random variables
Signal denoising
Signal processing
Signal restoration
Upper bound
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Beschreibung
Zusammenfassung:In this paper, a new thresholding approach for data denoising is presented. The approach is based minimum noiseless description length (MNDL), a new method for optimum sub-space selection in data representation. By using the observed noisy data, this information theoretic approach provides the optimum threshold that minimizes the description length of the noiseless signal. Comparison of the new method with the existing thresholding methods is provided
DOI:10.1109/CIISP.2007.369308