Title :
A novel inter-scale correlation image denoising method based on Dual-tree M-band wavelet
Author :
Yan, Jingwen ; Yang, Guide ; Zhang, Anfa
Author_Institution :
Inst. of Technol., Shantou Univ., Shantou, China
Abstract :
A novel inter-scale correlation image denoising method based on dual-tree M-band wavelet (DTT) is proposed in this paper. Dual-tree M-band wavelet transform is a shift-invariant, multi-scale and multi-direction transform based on a Hilbert pair of wavelets initially proposed by N. Kingsbury. Improving upon Xu¿s denosing algorithm based on wavelet inter-scale correlation, a new correlation modeling is provided between each high frequency detail subimage and corresponding M subimages in adjacent lower frequency scale. In the new algorithm, signal and noise are distinguished by the strength of the correlation, and combined with threshold functions. The experiment result shows that comparing with the classical denoising methods, for example, wavelet denoising method, Dual-tree complex wavelet denoising method, contourlet denoising method and so on..., the proposed denoising method achieves an excellent balance between suppressing noise effectively and preserving as many image details and edges as possible.
Keywords :
Hilbert transforms; correlation methods; image denoising; trees (mathematics); wavelet transforms; Hilbert pair; dual-tree M-band wavelet; inter-scale correlation image denoising; multi-direction transform; multi-scale transform; shift-invariant transform; wavelet denoising; Discrete transforms; Discrete wavelet transforms; Frequency; Image denoising; Image edge detection; Intelligent systems; Knowledge engineering; Noise reduction; Signal processing; Wavelet transforms;
Conference_Titel :
Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-2196-1
Electronic_ISBN :
978-1-4244-2197-8
DOI :
10.1109/ISKE.2008.4730912