Iterative Regularization Model for Image Denoising Based on Dual Norms

Guan Nan Chen; Dan Er Xu; Rong Chen; Zu Fang Huang; Zhong Jian Teng

doi:10.4028/www.scientific.net/AMM.182-183.1245

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 182-183Iterative Regularization Model for Image Denoising...

Iterative Regularization Model for Image Denoising Based on Dual Norms

Abstract:

Image denoising algorithm based on gradient dependent energy functional often compromised the image features like textures or certain details. This paper proposes an iterative regularization model based on Dual Norms for image denoising. By using iterative regularization model, the oscillating patterns of texture and detail are added back to fit and compute the original Dual Norms model, and the iterative behavior avoids overfull smoothing while denoising the features of textures and details to a certain extent. In addition, the iterative procedure is proposed in this paper, and the proposed algorithm also be proved the convergence property. Experimental results show that the proposed method can achieve a batter result in preserving not only the features of textures for image denoising but also the details for image.

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Periodical:

Applied Mechanics and Materials (Volumes 182-183)

Pages:

1245-1249

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.182-183.1245

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Online since:

June 2012

Authors:

Guan Nan Chen, Dan Er Xu, Rong Chen, Zu Fang Huang, Zhong Jian Teng

Keywords:

Dual Norms, Image De-Noising, Iterative Regularization Model

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References

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