An Optional Gauss Filter Image Denoising Method Based on Difference Image Fast Fuzzy Clustering
Xi Wen Liu, Chao Ying Liu · Applied Mechanics and Materials · 2013
Gaussian filtering algorithm has the defect that it will cause a blur at the image edges, therefore, an optional Gauss filter denoising method based on difference image fast fuzzy clustering is proposed. In this method, Gauss filtered image is firstly calculated, the difference image between the original image and the Gauss filtered image is acquired hereafter; and then fast FCM clustering of the Gauss filter image is carried out, the image histogram frequencies are taken as weighting coefficients of objective function when clustering, therefore the noise points of the original image are gotten; finally, optional Gauss filtering algorithm is applied to these noise points of the original image. Experiment results show that this method is fast and effective, its anti-disturbance performance is well, and it can effectively prevent edges from being blurred.