An Image Denoising Algorithm Using Adaptive Multiscale Products Thresholding
Zhang Wen-ge①②; Liu Fang①②; Gao Xin-bo②③; Jiao Li-cheng②③
①School of Computer Science and Technology, Xidian University, Xi’an 710071, China; ②Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an 710071, China; ③Institute of Intelligent Information Processing, Xidian University, Xi’an 710071, China
Abstract：An adaptive thresholding algorithm for natural image denoising is proposed in this paper, which is based on Stationary Wavelet Transform (SWT) and multiscale products. Different from traditional thresholding denoising algorithm, this threshold is imposed on multiscale products instead of imposed on wavelet coefficients directly. The characteristics of multiscale products of noisy image in SWT domain are analyzed, and an adaptive threshold estimator is proposed. The multiscale products intensify the important structure information of images and weaken the noise, and reach the result of both effective denoising and preserving the edges and details of image simultaneously. Experimental results show that the visual effect and the performance index of proposed algorithm outperform the adaptive multiscale products threshold denoising in dyadic wavelet domain.
2009, Vol. 31 
