CIDER: corrected inverse-denoising filter for image restoration

Authors:
You-Wei Wen;Michael Ng;Wai-ki Ching
Affiliations:
College of Science, South China Agricultural University, Guangzhou, P.R. China;Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, P.R. China;Department of Mathematics, The University of Hong Kong, Hong Kong, P.R. China
Venue:
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Year:
2007

Citing 6
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Abstract

In this paper we propose and develop a new algorithm, Corrected Inverse-Denoising filtER (CIDER) to restore blurred and noisy images. The approach is motivated by a recent algorithm ForWaRD, which uses a regularized inverse filter followed by a wavelet denoising scheme. In ForWaRD, the restored image obtained by the regularized inverse filter is a biased estimate of the original image. In CIDER, the correction term is added to this restored image such that the resulting one is an unbiased estimator. Similarly, the wavelet denoising scheme can be applied to suppress the residual noise. Experimental results show that the performance of CIDER is better than other existing methods in our comparison study.