1.Hubei Power Grid Intelligent Control and Equipment Engineering Technology Research Center， Hubei University of Technology， Wuhan 430068； China；2.Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System， Hubei University of Technology， Wuhan 430068， China
Abstract：The traditional dictionary-based signal line denoising method for transmission lines is vulnerable to the redundancy dictionary and causes insufficient restoration of the edge details of reconstructed images. In order to filter out the Gaussian noise existing on the surface of transmission line image effectively， an image denoising method combining non-local self-similarity of image and K-SVD (K-means and Singular Value Decomposition) dictionary learning algorithm is proposed. Similarity is used as a regular term constraint and weighted processing to improve the quality of denoising image restoration. The experiment selects several typical defects (broken strands， wear， bubbles) of the transmission line for simulation test. The experimental results show that the proposed algorithm can not only preserve the image texture features and edge details， but also has good robustness to Gaussian noise.
2020, Vol. 54 
