Catenary image enhancement using wavelet-based contourlet transform with cycle translation

The image quality is extremely important in the catenary fault diagnosis based on the image processing. In order to improve image visual effects, this paper proposes a catenary image enhancement method based on the wavelet-based contourlet transform (WBCT) with cycle translation. First, the Laplacian pyramid (LP) transform is replaced by the wavelet transform (WT) for reducing the redundancy of the contourlet transform (CT). Meanwhile, combine the WBCT with cycle translation to overcome the problem of WBCT without the translational invariance. Finally, the adaptive enhancement function is chosen to enhance the catenary images. Experimental results show that the proposed method has the advantages of preserving image edge details and texture. In terms of visual effects, signal-to-noise ratio (SNR) and edge preserving index (EPI), the proposed algorithm outperforms the traditional methods.