Multiscale blind image restoration using a wavelet decomposition

A multiscale blind image restoration scheme using a wavelet decomposition is presented. The proposed algorithm uses a wavelet decomposition to decompose the degradation model g=Df+w into smaller subband degradation models. Although the subband degradation models are in fact coupled together, our procedure decouples them by estimating the coupling error e_s(D,f) and subtracting the estimate from the subband degraded image g_s. The expectation maximization (EM) algorithm is then applied to each subband signal to estimate simultaneously the subband blur operator D_s and the original undegraded subband image f_s. Due to the well-posed condition of the subband blur operator, common ringing artifact is suppressed and regularization which trades fidelity for stability is not necessary