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Proceedings Paper

Acceleration in iterative image restoration by manipulation of gain parameter
Author(s): Ezzatollah Salari; Prashant Vinayak Athavale
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Paper Abstract

One of the major disadvantages of the standard iterative image restoration is its linear rate of convergence. In this paper it is shown that for natural scenes and uniform space invariant distortion, we can attain acceleration in the iteration process. It has been shown here that, for standard iterative restoration, if we choose the gain parameter close to but less than its upper limit and then after some iterations reduce it to exactly half of its upper limit, a close estimation of the original image can be obtained in that particular iteration itself. This is due to the fact that the iterative step vectors get closer to the original image vector as the iteration progresses, with a linear rate of convergence. The advantage of using this approach is that the iteration process can be accelerated in any desired iteration. Reducing the gain parameter in an early stage of the iteration process can save processing time at the cost of accuracy. On the other hand, if we choose to reduce the gain parameter after an increased number of iterations, we can obtain a more accurate result using more processing time. This is a result of the fact that the angle between the iterative step vector and the original image vector approaches zero as we increase the number of iterations.

Paper Details

Date Published: 28 May 2003
PDF: 8 pages
Proc. SPIE 5014, Image Processing: Algorithms and Systems II, (28 May 2003); doi: 10.1117/12.473069
Show Author Affiliations
Ezzatollah Salari, Univ. of Toledo (United States)
Prashant Vinayak Athavale, Univ. of Toledo (United States)


Published in SPIE Proceedings Vol. 5014:
Image Processing: Algorithms and Systems II
Edward R. Dougherty; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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