NDLI: Entropy-based trilateral filtering for noise removal in digital images

Content Provider	IEEE Xplore Digital Library
Author	Herng-Hua Chang
Copyright Year	2010
Description	Author affiliation: Computational Biomedical Engineering Laboratory (CBEL), Department of Engineering Science and Ocean Engineering, National Taiwan University, Daan 10617 Taipei, Taiwan (Herng-Hua Chang)
Abstract	Bilateral filtering has been a popular denoising technique that smooths images while preserving edges by means of a nonlinear combination of adjacent pixel values. We propose an entropy-based trilateral (EnTri) filter that extends the classical bilateral filter for noise removal in digital images. A new median-metric weighting function is incorporated into the geometric and radiometric components, followed by an entropy function to balance the contribution between the weights. The entropy function is used to adaptively detect the local intensity variations on each pixel. Our EnTri framework replaces the intensity value on each pixel with an average value weighted by the three components between neighboring pixels. A variety of images contaminated with various levels of noise were used to assess the performance of this new filtering method. Experimental results indicate that the EnTri filter outperformed several existing methods in both visual image quality and restored signal quantity.
Starting Page	673
Ending Page	677
File Size	3066760
Page Count	5
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5647219
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	PSNR Noise reduction Boats Entropy Image restoration Pixel
Content Type	Text
Resource Type	Article

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