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Color image restoration with Fuzzy Gaussian mixture model driven nonlocal filter

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dc.contributor.author Surya Prasath V.
dc.contributor.author Delhibabu R.
dc.date.accessioned 2018-09-18T20:27:35Z
dc.date.available 2018-09-18T20:27:35Z
dc.date.issued 2015
dc.identifier.issn 1865-0929
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/140106
dc.description.abstract © Springer International Publishing Switzerland 2015. Color image denoising is one of the classical image processing problem and various techniques have been explored over the years. Recently, nonlocal means (NLM) filter is proven to obtain good results for denoising Gaussian noise corrupted digital images using weighted mean among similar patches. In this paper, we consider fuzzy Gaussian mixture model (GMM) based NLM method for removing mixed Gaussian and impulse noise. By computing an automatic homogeneity map we identify impulse noise locations and utilize an adaptive patch size. Experimental results on mixed noise affected color images show that our scheme performs better than NLM, anisotropic diffusion and GMM-NLM over different noise levels. Comparison with respect to structural similarity, color image difference, and peak signal to noise ratio error metrics are undertaken and our scheme performs well overall without generating color artifacts.
dc.relation.ispartofseries Communications in Computer and Information Science
dc.subject Gaussian mixture
dc.subject Image denoising
dc.subject Mixed noise
dc.subject Nonlocal means
dc.subject Type-2 fuzzy sets
dc.title Color image restoration with Fuzzy Gaussian mixture model driven nonlocal filter
dc.type Conference Paper
dc.relation.ispartofseries-volume 542
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 137
dc.source.id SCOPUS18650929-2015-542-SID84951875211


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  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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