## 598 – Upcoming talk: Leming Qu

November 3, 2009

Leming Qu, Wed. November 11, 2:40-3:30 pm, MG 120.

Wavelet Image Restoration and Regularization Parameters Selection

For the restoration of an image based on its noisy distorted observations, we propose wavelet domain restoration by a scale-dependent $L^1$ 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) are 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.