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Proceedings Paper

An efficient adaptive total variation regularization for image denoising for mobile communication in 5G
Author(s): Haiqi Jiang
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Paper Abstract

The regularization method has recently been an efficient approach to make the process of image denoising wellposed, while preserving image textures and details become more intractable. However, when it's applied to image denoising industry in 5G environment, iterative computation time for TV variation regularization algorithm must be reduced, considering the requirements for practicability. In this paper, a fast algorithm based on Chambolle dual factors is presented and denoising duration of TV denoising model is improved by reducing stopping criteria for iteration on the premise of unchanged denoising effect based on the utility concept. In addition, evaluation methods for the edge protection effect are improved and personal subjective factors brought by traditional evaluation methods are reduced. Furthermore, numerical experiments show that the proposed method can achieve better results in removing the noise, restraining staircase effect, preserving directional texture as well as significantly reduce denoising duration.

Paper Details

Date Published: 29 August 2016
PDF: 7 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100331W (29 August 2016); doi: 10.1117/12.2243635
Show Author Affiliations
Haiqi Jiang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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