Optical Review

, Volume 23, Issue 3, pp 460–469 | Cite as

Rician noise reduction in magnetic resonance images using adaptive non-local mean and guided image filtering

  • Muhammad Tariq Mahmood
  • Yeon-Ho Chu
  • Young-Kyu Choi
Regular Paper
First Online:
Received:
Accepted:

Abstract

This paper proposes a Rician noise reduction method for magnetic resonance (MR) images. The proposed method is based on adaptive non-local mean and guided image filtering techniques. In the first phase, a guidance image is obtained from the noisy image through an adaptive non-local mean filter. Sobel operators are applied to compute the strength of edges which is further used to control the spread of the kernel in non-local mean filtering. In the second phase, the noisy and the guidance images are provided to the guided image filter as input to restore the noise-free image. The improved performance of the proposed method is investigated using the simulated and real data sets of MR images. Its performance is also compared with the previously proposed state-of-the art methods. Comparative analysis demonstrates the superiority of the proposed scheme over the existing approaches.

Keywords

Magnetic resonance images Rician noise Guided image filtering Non-local mean Noise reduction 
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Notes

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) Grant funded by the Ministry of Science, ICT and Future Planning (MSIP) (2013R1A1A2008180).

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Copyright information

© The Optical Society of Japan 2016

Authors and Affiliations

  • Muhammad Tariq Mahmood
    • 1
  • Yeon-Ho Chu
    • 1
  • Young-Kyu Choi
    • 1
  1. 1.School of Computer Science and EngineeringKorea University of Technology and EducationCheonanKorea

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