Noise diagnosis and fuzzy filter design for image processing using Matlab
Abstract (Base Paper):
In this paper, a novel noise classifier using data mining techniques and fuzzy median-mean filter for removing complex noise from corrupted images is proposed. The fuzzy median-mean filter combining a median-type filter with a mean filter is able to effectively recover images corrupted by Gaussian plus salt-and-pepper noise. The performance of the proposed approach is evaluated and compared with the classical median filter, mean filter and fuzzy filter algorithms for both salt and pepper noise and Gaussian noise removal tasks. The quantitative and qualitative results on test images demonstrate that the proposed approach can remove the noise effectively while preserving the image local features, even at a very high impulse noise and Gaussian noise level.
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