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《Journal of Minnan Normal University(Natural Science)》 2018-03
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A Fast Image Denoising Method by Quaternion Total Variation

CHEN Yuqun;CHEN Yingpin;LIN Fan;WANG Lingzhi;School of Physics and Information Engineering, Minnan Normal University;  
Image denoising is an important problem in image processing. Among many approaches, the total variation has attracted great attention because of its nice mathematical interpretation. Traditional total variation explores the vertical and horizontal directions and the number of directions can be increased to further improve denoising performance. The resulting challenge is higher computation since multiple constraints are introduced in denoising model. This work first transforms the quaternion total variation constraints problem in the spatial domain into a problem in the frequency domain by using the fast Fourier transform and the convolution theorem. Then, it incorporates the split Bregman iterations to enable fast image denoising. The effectiveness and the computation efficiency are verified by the comparisons with other methods including state-of-the-art methods.
【Fund】: 福建省教育厅中青年教师教育科研项目(JAT170352);; 广东省数字信号与图像处理技术重点实验室开放课题(2017GDDSIPL_01)
【CateGory Index】: TP391.41
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