Image denoising study based on balanced multiwavelet

Lingyuan Li; Zhengqiang Wang; Lixin Song

doi:10.1117/12.838093

30 October 2009 Image denoising study based on balanced multiwavelet

Lingyuan Li, Zhengqiang Wang, Lixin Song

Proceedings Volume 7494, MIPPR 2009: Multispectral Image Acquisition and Processing; 749424 (2009) https://doi.org/10.1117/12.838093
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

The particular noise in image not only lower the quality of image but also make denoising more difficult. The multiwavelet with the orthogonality and symmetry decompose the image signal more precisely and denoise better than wavelet. But for multiwavelet transform, the choice of prefilter is extremely important, meanwhile leads to the complication of computation. Furthermore, the image decomposition based on balanced orthogonal multiwavelet is excellent, and does not need pre-filtering. So, in this paper, we propose a method of combining threshold-selecting model with semi-soft thresholding function for image denoising based on the coefficients of balanced orthogonal multiwavelet transform. The simulation results show that this method is superior to others.

Citation Download Citation

Lingyuan Li, Zhengqiang Wang, and Lixin Song "Image denoising study based on balanced multiwavelet", Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 749424 (30 October 2009); https://doi.org/10.1117/12.838093

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