On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering

In this paper, we focus on the problem of speckle removal by means of anisotropic diffusion and, specifically, on the importance of the correct estimation of the statistics involved. First, we derive an anisotropic diffusion filter that does not depend on a linear approximation of the speckle model...

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Bibliographic Details
Published in:IEEE transactions on image processing 2006-09, Vol.15 (9), p.2694-2701
Main Authors: Aja-Fernandez, S., Alberola-Lopez, C.
Format: Article
Language:English
Subjects:
Additive noise
Algorithms
Anisotropic diffusion
Anisotropic magnetoresistance
Anisotropy
Applied sciences
Approximation
Coefficient of variation
Computer Simulation
Detection, estimation, filtering, equalization, prediction
Diffusion
Equations
Exact sciences and technology
Filtering
Image enhancement
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
image restoration
Information Storage and Retrieval - methods
Information, signal and communications theory
Mathematical analysis
Models, Statistical
Noise
Noise reduction
Nonlinear filters
Reproducibility of Results
Sensitivity and Specificity
Signal and communications theory
Signal processing
Signal, noise
Speckle
speckle filtering
Statistics
statistics estimation
Telecommunications and information theory
Ultrasonic imaging
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Summary:In this paper, we focus on the problem of speckle removal by means of anisotropic diffusion and, specifically, on the importance of the correct estimation of the statistics involved. First, we derive an anisotropic diffusion filter that does not depend on a linear approximation of the speckle model assumed, which is the case of a previously reported filter, namely, SRAD. Then, we focus on the problem of estimation of the coefficient of variation of both signal and noise and of noise itself. Our experiments indicate that neighborhoods used for parameter estimation do not need to coincide with those used in the diffusion equations. Then, we show that, as long as the estimates are good enough, the filter proposed here and the SRAD perform fairly closely, a fact that emphasizes the importance of the correct estimation of the coefficients of variation
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2006.877360