1999
DOI: 10.1117/12.341091
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<title>Performance of nonlinear methods in medical image restoration</title>

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Cited by 9 publications
(2 citation statements)
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“…In the second step, fuzzy C-means 13 (FCM) optimization is used to update the centroids and the fuzzy membership values of the samples. AFLC has been tested and used for image segmentation, restoration, and compression as well as other pattern recognition tasks 4,14,15 . It has been consistently shown to be a very effective clustering algorithm for its good performance and fast execution.…”
Section: Vector Quantizationmentioning
confidence: 99%
“…In the second step, fuzzy C-means 13 (FCM) optimization is used to update the centroids and the fuzzy membership values of the samples. AFLC has been tested and used for image segmentation, restoration, and compression as well as other pattern recognition tasks 4,14,15 . It has been consistently shown to be a very effective clustering algorithm for its good performance and fast execution.…”
Section: Vector Quantizationmentioning
confidence: 99%
“…Image restoration is a common task in image processing with lots of real-world applications such as astronomical imaging [1], [2], medical imaging [3], [4] and so on. Generally speaking, the image degradation usually comes from the imaging process, e.g., the motion of imaging objects, sensing device and propagation perturbation of the atmosphere between the objects and sensing device [5].…”
Section: Introductionmentioning
confidence: 99%