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Wavelet Image Restoration and Regularization Parameters Selection

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1 Author(s)
Leming Qu ; Dept. of Math., Boise State Univ., Boise, ID, USA

For the restoration of an image based on its noisy distorted observations, we propose wavelet domain restoration by scale-dependent ¿1 penalized regularization method (WaveRSL1). The data adaptive choice of the regularization parameters is based on the Akaike Information Criterion (AIC) and the degrees of freedom (df) is estimated by the number of nonzero elements in the solution. Experiments on some commonly used testing images illustrate that the proposed method possesses good empirical properties.

Published in:

Frontier of Computer Science and Technology, 2009. FCST '09. Fourth International Conference on

Date of Conference:

17-19 Dec. 2009

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