Cyclic Image Denoising Algorithm Using Hybrid Thresholding Function

Sabahaldin A. Hussain, Sami M. Gorashi


In this paper a cyclic denoising algorithm which integrates spatial domain bilateral filter and hybrid thresholding function in the wavelet domain is proposed. The wavelet transform is used to decompose the noisy image into approximation and detail subband. The noisy image is firstly pre-processed using spatial bilateral filter. Secondly, Bayesian based threshold calculation that uses hybrid thresholding function is applied to the detail subband. Thirdly, a sub image is constructed from approximation and detail subband at each level and then cyclically filtered using spatial bilateral filter. The depth of cyclic filtering is equal to the number of decomposition level. The experimental results show that the performance of the proposed denoising algorithm is superior to that of the conventional denoising approach and can deal with both low and high frequency noise components efficiently.


Keywords: Image denoising; Thresholding function; Cyclic filter.

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