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Adaptive weighted mean filtering algorithm based onconfidence interval(PDF)


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Adaptive weighted mean filtering algorithm based onconfidence interval
Chen Jiayi1Huang Nan2Xiong Gangqiang1Cao Huiying1Xu Qiuyan3
1.School of Information Engineering,Guangdong Medical University,Zhanjiang 524023,China; 2.School of Science,Nanjing University of Science and Technology,Nanjing 210094,China; 3.Surgical Intensive Care Unit,Center People’s Hospital of Zhanjiang,Zhanjiang 524037,China
confidence interval mean filtering algorithm adaptive filtering algorithm Gaussian noise gray correlation distance correlation
An adaptive weighted mean filtering algorithm based on a confidence interval is proposed to improve the results of filtered images.The weighted means of the pixels in a filtering window and within the confidence interval are calculated according to the characteristics of Gaussian noise and its effect on an original image.A weighted coefficient is obtained by the linear weighted sum of the gray measure factor and distance measure factor,and the gray correlation and distance correlation are taken into consideration.Finally,the gray of the weighted mean filtered image is equalized.The experimental results show that this algorithm is better than the standard mean filtering(SMF)algorithm and adaptive mean filtering(AMF)algorithm,the filtered image is clearer,the original image is recovered well,and the edges and details are kept; the normalized mean square error(NMSE)of this algorithm is lower than that of the SMF and AMF.


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Last Update: 2017-06-30