Quantitative analysis of artifacts in linear space-invariant image restoration

Several image restoration algorithms exist in the literature ranging from deterministic iterative techniques to optimum recursive methods. Unfortunately, all these algorithms produce undesirable artifacts in the process of undoing the degradations because of the ill-posed nature of the image restoration problem. This paper provides a complete quantitative analysis of different artifacts caused by linear shift-invariant (LSI) image restoration methods. The aim of this paper is to mathematically show how these artifacts originate in the general case of an arbitrary blur point spread function and an arbitrary LSI restoration filter, and then to study the characteristics of these artifacts in the special cases of uniform motion blur and out-of-focus blur via experimental analysis. Several pictures that illustrate these artifacts are presented. We discuss strategies for the suppression of these artifacts based on the analysis provided.

[1]  M. Ibrahim Sezan,et al.  Prototype image constraints for set-theoretic image restoration , 1991, IEEE Trans. Signal Process..

[2]  A. Murat Tekalp,et al.  Adaptive image restoration with artifact suppression using the theory of convex projections , 1990, IEEE Trans. Acoust. Speech Signal Process..

[3]  A. Murat Tekalp,et al.  Edge-adaptive Kalman filtering for image restoration with ringing suppression , 1989, IEEE Trans. Acoust. Speech Signal Process..

[4]  B. R. Hunt,et al.  Digital Image Restoration , 1977 .

[5]  Reginald L. Lagendijk,et al.  Regularized iterative image restoration with ringing reduction , 1988, IEEE Trans. Acoust. Speech Signal Process..

[6]  A. M. Tekalp,et al.  Iterative image restoration with ringing suppression using the method of POCS , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[7]  Jan Biemond,et al.  Boundary value problem in image restoration , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.