HeNLM-LA3D: A three-dimensional locally adaptive Hermite functions expansion based non-local means algorithm for CT applications

A three-dimensional filtering algorithm for CT images (HeNLM-LA3D) has been proposed that is based on expanding the pixel neighborhood into Hermite functions, which form an orthonormal basis. Accounting for Hermite functions properties, pixel neighborhoods are oriented according to principal compone...

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Bibliographic Details
Published in:Pattern recognition and image analysis 2015-10, Vol.25 (4), p.658-668
Main Authors: Mamaev, N. V., Lukin, A. S., Yurin, D. V.
Format: Article
Language:English
Subjects:
Algorithms
Applied Problems
Computational mathematics
Computer Science
Image Processing and Computer Vision
Image processing systems
Medical imaging
Neighborhoods
Noise
Pattern Recognition
Principal components analysis
Radiation
Studies
Tomography
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Summary:A three-dimensional filtering algorithm for CT images (HeNLM-LA3D) has been proposed that is based on expanding the pixel neighborhood into Hermite functions, which form an orthonormal basis. Accounting for Hermite functions properties, pixel neighborhoods are oriented according to principal components of the structure tensor. The filtering parameter is adaptively adjusted to local estimates of the noise level. A noise estimation algorithm is proposed.
ISSN:1054-6618
1555-6212
DOI:10.1134/S105466181504015X