Image Denoising in Industry Based on Multiwavelet Riesz Bases

Qi Chao Song; Zhi Song Liu; Chao Ping Wang

doi:10.4028/www.scientific.net/AMR.675.59

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 675Image Denoising in Industry Based on Multiwavelet...

Image Denoising in Industry Based on Multiwavelet Riesz Bases

Abstract:

Damage testing of components is a key point in many industry fields. In some cases, endoscope is used to inspect the damage part, while the images are often noised. In this paper, we focus on industrial image denoising based on multiwavelet Riesz bases. Starting from compactly supported vector refinement equation, we provide a characterization to form two Riesz bases and an example is given. Based on example Riesz bases, we research industrial endoscope image denoising and get satisfying result.

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Periodical:

Advanced Materials Research (Volume 675)

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59-62

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.675.59

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Online since:

March 2013

Authors:

Qi Chao Song, Zhi Song Liu, Chao Ping Wang

Keywords:

Image De-Noising, Industrial Endoscope, Multiwavelet, Riesz Bases

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References

[1] Z. Averbuch and V. A. Zheludev: A new family of spline-based biorthogonal wavelet transforms and their applications to image compression, IEEE Trans. Image Process. 13 (2004), 993-1007.

DOI: 10.1109/tip.2004.827229

Google Scholar

[2] Cohen and I. Daubechies: A new technique to estimate the regularity of refinable funtions, Rev. Mat. Iberoamericana. 12(1996), 527-591.

DOI: 10.4171/rmi/207

Google Scholar

[3] W. Dahmen: Wavelet and multiscale methods for operator equations, ACTA Numer. 6 (1997), 55-228.

Google Scholar

[4] Daubechies: Ten Lectues on Wavelets, CMBS-NSF Series in Applied Mathematics, SIAM. Philadelphia, (1992).

Google Scholar

[5] C. K. Chui and J. A. Lian: A study of orthogonal multi-wavelets, Appl. Numer. Math. 20 (1996), 273-298.

Google Scholar

[6] B. Han and R. Q. Jia: Characterization of Riesz bases of wavelets generated from multiresolution analysis, Appl. Comput. Harmon. Anal. 23 (2007), 321-345.

DOI: 10.1016/j.acha.2007.02.001

Google Scholar

[7] R. Q. Jia: Convergence of vector subdivision schemes and construction of biorthogonal multip wavelets, in: K. S. Lau(ed. ), Advance in wavelets. Singapore: Springer-Verlag, (1999) 199-227.

Google Scholar

[8] S. Li and Z. S. Liu: Riesz Multiwavelet Bases Generated by Vector Riefinement Equation, Sci. China Ser. A, 51(3), (2009).

DOI: 10.1007/s11425-008-0118-8

Google Scholar

[9] R. Q. Jia, J. Z. Wang and D. X. Zhou: Compactly supported wavelet bases for Sobolev spaces, Appl. Comput. Harmon. Anal. 15(2003) 224-241.

DOI: 10.1016/j.acha.2003.08.003

Google Scholar

[10] R. L. Long, D. R . Chen: Biorthogonal wavelet bases on Appl. Comput. Harmon. Anal. 2 (1995), 230-242.

Google Scholar