Improved Anisotropic Gaussian Filters

• URL: http://arxiv.org/abs/2303.13278v2
• Date: Wed, 4 Oct 2023 13:35:36 GMT
• Title: Improved Anisotropic Gaussian Filters
• Authors: Alex Keilmann, Michael Godehardt, Ali Moghiseh, Claudia Redenbach, Katja Schladitz
• Abstract summary: Elongated anisotropic Gaussian filters are used for the orientation estimation of fibers. This paper proposes a modified algorithm for 2D anisotropic Gaussian filters and shows that this improves their precision.
• Score: 1.2499537119440245
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Elongated anisotropic Gaussian filters are used for the orientation estimation of fibers. In cases where computed tomography images are noisy, roughly resolved, and of low contrast, they are the method of choice even if being efficient only in virtual 2D slices. However, minor inaccuracies in the anisotropic Gaussian filters can carry over to the orientation estimation. Therefore, this paper proposes a modified algorithm for 2D anisotropic Gaussian filters and shows that this improves their precision. Applied to synthetic images of fiber bundles, it is more accurate and robust to noise. Finally, the effectiveness of the approach is shown by applying it to real-world images of sheet molding compounds.

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