Speckle reducing anisotropic diffusion

• Published in: IEEE transactions on image processing Vol. 11; no. 11; pp. 1260 - 1270
• Main Authors: Yongjian Yu, Acton, S.T.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2002; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive filters; Additive noise; Algorithms; Anisotropic magnetoresistance; Anisotropy; Applied sciences; Carotid arteries; Computer simulation; Diffusion; Exact sciences and technology; Frost; Image processing; Information, signal and communications theory; Laplace equations; Partial differential equations; Radar imaging; Reduction; Signal processing; Speckle; Studies; Telecommunications and information theory; Ultrasonic testing; Ultrasonic variables measurement; Performance evaluation; Filtering; Image processing; Noise reduction; Speckle; Partial differential equation; Ultrasonic imaging; Algorithm performance; Radar imaging; Anisotropic scattering; Edge detection; Image enhancement; Synthetic aperture radar
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2002.804276

This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications. SRAD is the edge-sensitive diffusion for speckled images, in the same way that conventional anisotropic diffusion is the edge-sensitive diffusion for images corrupted with additive noise. We first show that the Lee and Frost filters can be cast as partial differential equations, and then we derive SRAD by allowing edge-sensitive anisotropic diffusion within this context. Just as the Lee (1980, 1981, 1986) and Frost (1982) filters utilize the coefficient of variation in adaptive filtering, SRAD exploits the instantaneous coefficient of variation, which is shown to be a function of the local gradient magnitude and Laplacian operators. We validate the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery. We also demonstrate the algorithm performance with real SAR data. The performance measures obtained by means of computer simulation of carotid artery images are compared with three existing speckle reduction schemes. In the presence of speckle noise, speckle reducing anisotropic diffusion excels over the traditional speckle removal filters and over the conventional anisotropic diffusion method in terms of mean preservation, variance reduction, and edge localization.