Abstract
Digital processing techniques have been widely utilized for the restoration of blurred and noisy images <1>. The major limitations associated with such techniques arise from the large dimensionality of practical images. Large dimensionality not only leads to lengthy processing, but more importantly, creates problems of numerical instability.
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References
M. M. Sondhi, “Image Restoration: The Removal of Spatially Invariant Degradations,” Proceedings of the IEEE, Vol. 60, No. 7, July 1972, or,. 842–853.
W.K. Pratt and F. Davarian, ’’Fast Computational Techniques for Pseudoinverse and Wiener Image Restoration,“IEEE Transactions on Computers (to be published).
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W. K. Pratt, Digital Image Processing, Wiley, New York, 1977.
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© 1978 Springer Science+Business Media New York
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Pratt, W.K. (1978). Pseudoinverse Image Restoration Computational Algorithms. In: Barrekette, E.S., Stroke, G.W., Nesterikhin, Y.E., Kock, W.E. (eds) Optical Information Processing. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-7545-0_19
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DOI: https://doi.org/10.1007/978-1-4615-7545-0_19
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