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Stefan cel Mare
University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  4/2018 - 12

 HIGHLY CITED PAPER 

Wavelet-Based Adaptive Anisotropic Diffusion Filter

TANYERI, U. See more information about TANYERI, U. on SCOPUS See more information about TANYERI, U. on IEEExplore See more information about TANYERI, U. on Web of Science, DEMIRCI, R. See more information about DEMIRCI, R. on SCOPUS See more information about DEMIRCI, R. on SCOPUS See more information about DEMIRCI, R. on Web of Science
 
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Download PDF pdficon (2,147 KB) | Citation | Downloads: 1,134 | Views: 2,728

Author keywords
image denoising, discrete wavelet transforms, anisotropic, adaptive filters, nonlinear filters

References keywords
image(19), processing(16), diffusion(14), speckle(12), anisotropic(12), wavelet(7), images(7), filter(6), reduction(5), filtering(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-11-30
Volume 18, Issue 4, Year 2018, On page(s): 99 - 106
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.04012
Web of Science Accession Number: 000451843400012
SCOPUS ID: 85058776237

Abstract
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Its multiplicative nature complicates speckle noise reduction in images because of the effort required for separation of noisy pixels from other pixels. In this study, a novel adaptive anisotropic diffusion filter algorithm based on Haar wavelet transform has been proposed. Initially, Haar transform of image to be filtered was taken and then median absolute deviation of wavelet coefficients was used to tune the conductance parameter, K of diffusion filter with different diffusion functions. The suggested strategy has been tested with different images and different noise variances. Moreover, experimental results have been compared with conventional diffusion filters, and also Lee filter and Wiener filter which are frequently used for despeckling.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 57,994 TCR
SCOPUS® Citations for all references: 72,840 TCR

Web of Science® Average Citations per reference: 1,611 ACR
SCOPUS® Average Citations per reference: 2,023 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-04-13 18:27 in 177 seconds.




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