| Image decomposition using adaptive regularization and div （BMO） |
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| 作者姓名： | Chengwu Lu Guoxiang Song |
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| 作者单位： | [1]School of Mathematics and Statistics, Chongqing University of Arts and Sciences, Chongqing 402160, E R. China [2]School of Science, Xidian University, Xi＇ an 710071, E R. China |
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| 基金项目： | This work was supported by the Science and Technology Foundation Program of Chongqing Municipal Education Committee （K J091208）. |
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| 摘 要： | In order to avoid staircasing effect and preserve small scale texture information for the classical total variation regularization, a new minimization energy functional model for image decomposition is proposed. Firstly, an adaptive regularization based on the local feature of images is introduced to substitute total variational regularization. The oscillatory component containing texture and/or noise is modeled in generalized function space div (BMO). And then, the existence and uniqueness of the minimizer for proposed model are proved. Finally, the gradient descent flow of the Euler-Lagrange equations for the new model is numerically implemented by using a finite difference method. Experiments show that the proposed model is very robust to noise, and the staircasing effect is avoided efficiently, while edges and textures are well remained.
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| 关 键 词： | image decomposition regularization total variation space div (BMO) |
Image decomposition using adaptive regularization and div (BMO) |
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| Chengwu Lu,Guoxiang Song.Image decomposition using adaptive regularization and div (BMO)[J].Journal of Systems Engineering and Electronics,2011,22(2):358-364. |
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| Authors: | Chengwu Lu Guoxiang Song |
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| Institution: | 1. School of Mathematics and Statistics, Chongqing University of Arts and Sciences, Chongqing 402160, P. R. China;School of Science, Xidian University, Xi'an 710071, P. R. China
2. School of Science, Xidian University, Xi'an 710071, P. R. China |
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| Abstract: | In order to avoid staircasing effect and preserve small scale texture information for the classical total variation regularization, a new minimization energy functional model for image decomposition is proposed.Firstly, an adaptive regularization based on the local feature of images is introduced to substitute total variational regularization. The oscillatory component containing texture and/or noise is modeled in generalized function space div (BMO). And then, the existence and uniqueness of the minimizer for proposed model are proved. Finally, the gradient descent flow of the Euler-Lagrange equations for the new model is numerically implemented by using a finite difference method.Experiments show that the proposed model is very robust to noise, and the staircasing effect is avoided efficiently, while edges and textures are well remained. |
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| Keywords: | image decomposition regularization total variation space div (BMO) |
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