Paper
28 May 2003 Acceleration in iterative imbased on the above performance, age restoration by manipulation of gain parameter
Ezzatollah Salari, Prashant Vinayak Athavale
Author Affiliations +
Proceedings Volume 5014, Image Processing: Algorithms and Systems II; (2003) https://doi.org/10.1117/12.473069
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States
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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ezzatollah Salari and Prashant Vinayak Athavale "Acceleration in iterative imbased on the above performance, age restoration by manipulation of gain parameter", Proc. SPIE 5014, Image Processing: Algorithms and Systems II, (28 May 2003); https://doi.org/10.1117/12.473069
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KEYWORDS
Distortion

Image restoration

Signal to noise ratio

Point spread functions

Image processing

Imaging systems

Image filtering

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