Journal of Chemical and Pharmaceutical Research (ISSN : 0975-7384)

Reach Us reach to JOCPR whatsapp-JOCPR +44 1625708989
All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.

Original Articles: 2014 Vol: 6 Issue: 6

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


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

rtp slot demo