The Contourlet Transform with Multiple Cycles Spinning for Catenary Image Denoising - Changdong Wu; Zhigang Liu; Hua Jiang (Indonesian Journal of Electrical Engineering and Computer Science, 2014)
In the catenary images, noise and artifacts are introduced due to the acquisition techniques and systems, which may influence the judgement of catenary quailty and working states. In this paper, the contourlet transform (CT) with performances of multi-scale, multi-resolution and anisotropy is proposed, which can be effectively applied to image denoising. However, the CT hasn’t the spinning invariance, which will lead to the Gibbs-like phenomena. In this paper, the CT with multiple cycle spinning is introduced for image denoising, which can effectively eliminate the visual artifacts due to the lack of translational invariance. Meanwhile, the different Laplacian pyramid (LP) filters and directional filter banks (DFB) are proposed to test noisy images. Finally, test the influence of cycle spinning numbers for denoising effects by using different cycle spinning times. The experiment results show that the proposed method has excellent denoising performance in terms of the signal-to-noise ratio (SNR) and the visual effects, which is also superior to some other existing methods in overcoming the Gibbs-like phenomena, background smoothing and preservation of edge sharpness and texture. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4446