Ning Y.,Luoyang Research Institute of Electro optical Equipment |
Li L.,Zhengzhou Institute of Aeronautical Industry Management |
Shi H.,Xiamen University |
Chen J.,Xiamen University
Advanced Materials Research | Year: 2012
In this paper, an image de-noising algorithm based on the Dual-Tree Complex Wavelet Transform (DT-CWT) is proposed, which takes the advantage of redundant coefficients transformed by DT-CWT. The model of bivariate shrinkage function is used to provide a nonlinear threshold strategy. It exploits the dependency between inter-scale parents and children coefficients to recover the original coefficients more accurate. With the shift-invariance property of DT-CWT coefficients, the algorithm prevents the Gibbs effect caused by the thresholding, which further improves the reconstructed quality. Experiment results show that the de-noised image using DT-CWT can achieve more than 1dB prior to DWT with impressive visual results. © (2012) Trans Tech Publications, Switzerland.