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Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 49, Iss. 36 — Dec. 20, 2010
  • pp: 6845–6849

Phase pattern denoising using a regularized cost function with complex-valued Markov random fields based on a discrete model

Yan-Hua Li, Shi-Liang Qu, Xiang-Jun Chen, and Zhi-Yong Luo  »View Author Affiliations

Applied Optics, Vol. 49, Issue 36, pp. 6845-6849 (2010)

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We present a simple and effective method for denoising phase patterns based on a discrete model. The proposed filtering method transforms the image denoising problem to solving the energy diffusion problem of a system with complex-valued fields. We establish an appropriate cost function that uses the discrete form of complex-valued Markov random fields. The attractiveness of the proposed filtering method includes three points: the first is that the filtering process can be easily implemented using an iterative method, the second is that 2 π phase jumps are well preserved, and the third is its little computational effort. The performance of the proposed method is demonstrated by simulated and experimentally obtained phase patterns.

© 2010 Optical Society of America

OCIS Codes
(100.3008) Image processing : Image recognition, algorithms and filters
(110.3175) Imaging systems : Interferometric imaging

ToC Category:
Image Processing

Original Manuscript: August 30, 2010
Revised Manuscript: November 5, 2010
Manuscript Accepted: November 6, 2010
Published: December 13, 2010

Yan-Hua Li, Shi-Liang Qu, Xiang-Jun Chen, and Zhi-Yong Luo, "Phase pattern denoising using a regularized cost function with complex-valued Markov random fields based on a discrete model," Appl. Opt. 49, 6845-6849 (2010)

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