Title :
Image denoising algorithm based on edge feature extraction in curvelet domain
Author :
Wu, Jia-zhen ; Huang, Yong-dong
Author_Institution :
Inst. of Inf. & Syst. Sci., Beifang Univ. of Nat., Yinchuan, China
Abstract :
In order to overcome the shortcoming of the soft-threshold denosing method in curvelet domain, which may cause edges blurred, a new denoising method based on the edge features of the given image is proposed. In this method, we make full use of the anisotropie advantages of curvelet, extract the detail and edge information from the low-frequency domain and restore it, which can prevent the destruction of the soft-threshold. The results of simulation experiment show that this method can remove the noise and maintain the pictures´ edges well. Furthermore, it can improve the value of PSNR, and get better visual effect.
Keywords :
curvelet transforms; edge detection; feature extraction; image denoising; PSNR; curvelet domain; detail information extraction; edge feature extraction; edge information extraction; image denoising algorithm; low-frequency domain; soft-threshold denosing method; Feature extraction; Image edge detection; Noise; Noise reduction; Pattern recognition; Transforms; Wavelet analysis; Curvelet transform; Directional characteristics of edges; Feature extraction; Soft-thresholding denosing;
Conference_Titel :
Wavelet Analysis and Pattern Recognition (ICWAPR), 2012 International Conference on
Conference_Location :
Xian
Print_ISBN :
978-1-4673-1534-0
DOI :
10.1109/ICWAPR.2012.6294745