The similarity between different regions in an X-ray industrial computed tomography(CT) image of aeronautical engine turbine blade has been analyzed.A method called non-local means algorithm based on the similarity has been discussed to improve the industrial CT image contrast.This method adopts the weighted-Gaussian Euclidean distance to calculate the similarity between different regions in an image.Then it averages the regions with the similarity.It can decrease the noise in industrial CT images and meanwhile reserve the edge sharpness.However this method has a high computational complexity.So an acceleration algorithm based on Fourier transform for the non-local means algorithm has been researched.The weighted-Gaussian Euclidean distance is also replaced by the Euclidean distance to improve the calculation efficiency.The experiment results show that

this algorithm can improve the speed at least four times without affecting the denoising effect.