Název: Denoising 2-D vector fields by vector wavelet thresholding
Autoři: Westenberg, Michael A.
Ertl, Thomas
Citace zdrojového dokumentu: Journal of WSCG. 2005, vol. 13, no. 1, p. 33-40.
Datum vydání: 2005
Nakladatel: Václav Skala - UNION Agency
Typ dokumentu: article
článek
URI: http://wscg.zcu.cz/WSCG2005/Papers_2005/Journal/!WSCG2005_Journal_Final.pdf
http://hdl.handle.net/11025/1457
ISSN: 1213–6964 (online)
1213–6980 (CD-ROM)
1213–6972 (hardcover)
Klíčová slova: redukce šumu;vizualizace toku;2D vektorová pole
Klíčová slova v dalším jazyce: noise reduction;flow visualization;2D vector fields
Abstrakt: Noise reduction is an important preprocessing step for many visualization techniques that make use of feature extraction. We propose a method for denoising 2-D vector fields that are corrupted by additive noise. The method is based on the vector wavelet transform, which transforms a vector input signal to wavelet coefficients that are also vectors. We introduce modifications to scalar wavelet coefficient thresholding for dealing with vector-valued coefficients. We compare our wavelet-based denoising method with Gaussian filtering, and test the effect of these methods on the signal-to-noise ratio (SNR) of the vector fields before and after denoising. We also compare our method with component-wise scalar wavelet thresholding. Furthermore, we use a vortex measure to study the performances of the methods for retaining relevant details for visualization. The results show that for very low SNR, Gaussian filtering with large kernels has a slightly better performance than the wavelet-based method in terms of SNR. For larger SNR, the wavelet-based method outperforms Gaussian filtering, because Gaussian filtering removes small details that are preserved by the wavelet-based method. Component-wise denoising has a lower performance than our method.
Práva: © Václav Skala - UNION Agency
Vyskytuje se v kolekcích:Volume 13, Number 1-3 (2005)

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