A Non Local Means Method Using Fuzzy SimilarityCriteria for Restoration of Ultrasound Images
Publish Year: 1390
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICMVIP07_148
تاریخ نمایه سازی: 28 مرداد 1391
Abstract:
Conventional Non-Local Means (NLM) as one ofthe most powerful denoising filters especially for reduction ofadditive Gaussian noise is not successful in the case ofUltrasound (US) Images noise suppression. In the presence ofadditive Gaussian noise model, the NLM filter uses Euclideandistance similarity criterion to find similar patches andtherefore it is not appropriate for US images which have noisewith multiplicative and signal dependant nature. The moresuccessful version of NLM filter for US images which isknown as Optimized Bayesian NLM (OBNLM) is developedbased on Pearson Distance similarity criterion to measure andfind the similar patches. In this paper, we tried to improve theperformance of NLM filter using appropriate fuzzy similaritycriteria. The proposed filters are evaluated in objective andsubjective manners with both synthetic phantom and realclinical US images. It is shown that the proposed methodshave better ability for noise reduction comparing with theother state-of-art de-speckling filters.
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Authors
Kamran Binaee
DSP Research Laboratory, Department of Electrical Engineering, University of Guilan, Rasht, Iran
Reza P. R. Hasanzadeh
DSP Research Laboratory, Department of Electrical Engineering, University of Guilan, Rasht, Iran