Research of X-ray image fast de-noising method of power equipment based on GFNL algorithm

Zhanjie Lv, Jin Wang, Guiji Ta

Abstract

The method of X-ray fault detection is more widely in power equipment, for the effects of irradiation environment detection systems and X-ray images are subject to a variety of imaging noise disturbance, there will be a variety of poor contrast, poor uniformity background, ambiguity and large shortcomings. Currently used in the Poisson noise into white Gaussian noise methods and the use of wavelet shrinkage method will result in a large number of image detail is lost, the optimal parameters studied gradient X-ray image blur fast non-local means filtering de-noising (GFNL) method, which retain the original image details while effectively removing image noise, power failure has important implications for diagnostic equipment

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