Current Development in Theory and Applications of Wavelets
Volume 2, Issue 1, Pages 37 - 44
(April 2008)
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IMAGE DENOISING THROUGH SELF-ORGANIZING FEATURE MAP BASED ON NEIGHBOURING WAVELET COEFFICIENTS
Jianxin Dai (P. R. China) and Zhixin Li (P. R. China)
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Abstract:
This paper proposes a novel image denoising method through the self-organizing feature map (SOFM) which exploits spatial local correlation among image neighbouring wavelet coefficients. It is well known that wavelet coefficients are both intrascale and interscale statistical dependencies. SOFM algorithm is popular for unsupervised learning and data clustering and can capture persistence properties of wavelet coefficients. Experimental results show that the performance of the proposed method is practicable and effective for image denoising. |
| Keywords and phrases: self-organizing feature maps, image denoising, neighbouring wavelet coefficients. |
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