Wavelet Image Restoration and Regularization Parameters Selection

Leming Qu, Boise State University

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2009 Fourth International Conference on Frontier of Computer Science and Technology (FCST 2009), 17-19 December 2009, Piscataway, NJ. DOI: 10.1109/FCST.2009.18

Abstract

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.