Image Noise Reduction in Computed Tomography with Non-Local Means Algorithm Based on Adaptive Filtering Coefficients

To solve the over-smoothing problem of image details caused by fixed filtering coefficients during the filtering process in the traditional non-local means (NLM) algorithms, a weight function comprising an adaptive filtering coefficient is designed using the structural tensor (ST) trace as a discriminant criterion of image feature areas and called as ST-NLM. Meanwhile, to solve the time consuming problem of the traditional algorithms, the proposed algorithm is accelerated by integral images. The test results demonstrate that the overall smoothness and detail retention of images arc relatively good after denoising by the ST-NLM method. Compared with those by the NLM method, the peak signal-to-noise ratio, structural similarity, and running speed by the ST-NLM method increase by 3 dB, 5%, and twice, respectively.