Blind restoration of images degraded by space-variant blurs using iterative algorithms for both blur identification and image restoration

doi:10.1016/S0262-8856(96)01143-2

Image and Vision Computing

Volume 15, Issue 5, May 1997, Pages 399-410

https://doi.org/10.1016/S0262-8856(96)01143-2 Get rights and content

Abstract

This paper addresses the problem of digital blind restoration of images degraded by space-variant blurs and noise. The existing Expectation-Maximization (EM) algorithm reported in the literature is extended in this paper and combined with the region adaptive technique to handle the problem of identifying spatially variant blurs. The proposed algorithm is a two-step interative process. The expectation step of the EM algorithm is modified by the use of iterative image restoration. The entire image is divided into disjointed regions and the blur is identified in these regions using the proposed modified form of the EM algorithm. The iterative Constrained Least Squares (CLS) algorithm used in space-invariant image restoration is extended to restore the space variant blur images. Spatially adaptive algorithms for restoration are also applied. Experiments have been carried out to evaluate the performances of the proposed algorithms.

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Citation Excerpt :
This implementation enhanced the contrasts of images without much amplifying much the noise level in this ill-posed deconvolution problem. Authors in [6] used iterative Constrained Least Squares algorithm for both blur identification and image restoration in blind restoration of images degraded by space-variant blurs. They extended the Expectation–Maximization (EM) algorithm and combine it with the region adaptive technique to handle the problem of identifying spatially variant blurs.
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Regular paperBlind restoration of images degraded by space-variant blurs using iterative algorithms for both blur identification and image restoration

Abstract

Digital Image Restoration

Survey of recent developments in digital image restoration

Opt. Eng.

Iterative Identification and Restoration of Images

Review of image-blur models in a photographic system using the principles of optics

Opt. Eng.

Blind deconvolution of spatially invariant image blurs with phase

IEEE Trans. Acoust., Speech, Sig. Proc.

On statistical identification of a class of linear space-invariant blurs using non-minimum-phase ARMA models

IEEE Trans. Acoust., Speech, Signal Processing

Maximum likeli-hood from incomplete data via the EM algorithm

J. Roy. Stat. Soc.

Maximum likelihood blur identification and image restoration using the EM algorithm

IEEE Trans. Signal Processing

Simultaneous identification and restoration of images using Maximum Likelihood estimation and the EM algorithm

Maximum likelihood image identification and restoration based on the EM algorithm

Image identification and restoration of noisy blurred images using the Expectation-Maximization algorithm

IEEE Trans. Acoust., Speech Sig. Proc.

Simultaneous image identification and restoration using the EM-algorithm

Regular paper
Blind restoration of images degraded by space-variant blurs using iterative algorithms for both blur identification and image restoration