论文信息 - Recursive model-based image restoration

Recursive model-based image restoration

This paper presents a derivation of a fast recursive filter for image restoration if degradation obeys a linear degradation model with the unknown possibly non-homogeneous non-causal point-spread function. The degraded image is assumed to follow a causal simultaneous regressive model and the point-spread function is estimated using the local least-square estimate.

Michal Haindl | M. Haindl

[1] Bruce Fischl,et al. Learning an Integral Equation Approximation to Nonlinear Anisotropic Diffusion in Image Processing , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[2] D. Geman. Random fields and inverse problems in imaging , 1990 .

[3] Reginald L. Lagendijk,et al. Identification and restoration of noisy blurred images using the expectation-maximization algorithm , 1990, IEEE Trans. Acoust. Speech Signal Process..

[4] Mark Nitzberg,et al. Nonlinear Image Filtering with Edge and Corner Enhancement , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[5] Koichiro Deguchi,et al. Two-Dimensional Auto-Regressive Model , 1982 .

[6] Michal Haindl,et al. A scratch removal method , 1998, Kybernetika.

[7] R. Chellappa,et al. Digital image restoration using spatial interaction models , 1982 .

[8] Brian D. Jeffs,et al. Simple shape parameter estimation from blurred observations for a generalized Gaussian MRF image prior used in MAP image restoration , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[9] Michal Haindl. Recursive square-root filters , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[10] Donald Geman,et al. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .

[11] Michal Haindl,et al. A high-resolution radiospectrograph image reconstruction method. , 1996 .