Abstract：A fast method to reduce additive Gaussian noise in images was discussed. Some methods, like Nonlocal
Mean(NLM) and BM3D, perform very well in noise suppression but in them the block matching is carried
out, which results in huge computation and long running time. So they are not competent for work that has to
be finished in real time. In order to solve this problem, a kind of revised Butterworth function was proposed
to remove additive Gaussian noise in images through frequency domain. The numerical results showed that the
output of this method could preserve structures well in images after denoising when the noise magnitude was
not very big. Compared with the three methods, i.e. BM3D, total variation regularization and NLM, the Peak
Signal to Noise Ratio (PSNR) of the method was just a little smaller than Total variation regularization and
NLM. However, the running time it takes was only one fifth of them and was 1 000 times faster than NLM. So
it is suitable for huge number of image processings.
刘岳巍. 修正巴特沃斯函数快速图像降噪方法[J]. 《兰州大学学报（自科版）》, 2014, 50(1): 122-127.
LIU Yue-wei. A fast image denoising method with revised Butterworth function. JOURNAL OF LANZHOU UNIVERSITY(NATURAL SCIENCES), 2014, 50(1): 122-127.