Wavelet domain image restoration using adaptively regularized constrained total least squares

It is known that the adaptively regularized constrained total least squares (ARCTLS) outperforms the constrained total least squares (CTLS) or the regularized CTLS in image restoration. In this paper, a wavelet domain image restoration approach using ARCTLS is presented. The degraded image is first decomposed into subband images by using wavelet transform. The ARCTLS algorithm is then applied to each of the subband images. The proposed restoration method is simulated and compared with the conventional RCTLS and ARCTLS techniques. It is shown that the proposed method yields a better improved signal-to-noise ratio (SNR).