Restoration Algorithm for Gaussian Corrupted MRI Using Non-local Averaging

  • Aditya Srivastava
  • Vikrant Bhateja
  • Harshit Tiwari
  • S. C. Satapathy
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 340)

Abstract

Magnetic Resonance Images (MRI) are known to be corrupted by the additive Gaussian noise during the acquisition process. The presence of this noise affects the diagnosis as it tends to alter image details and pixel intensities. Conventional iterative denoising approaches fail to preserve the details and structures during MRI restoration. This paper proposes a Non-Local Averaging based MRI denoising algorithm to facilitate preservation of the finer structures. The proposed algorithm computes the weighted average of the similar pixels of the image within the local window. Method noise has been used as a measure for detail preservation which corresponds to the difference between original and the restored image. Simulation trials are performed on the image at differing levels of Gaussian noise which are then justified by method noise analysis and performance evaluation factors such as Peak Signal-Noise Ratio (PSNR) and Structural Similarity (SSIM). The proposed algorithm has demonstrated good performance, both in terms of visual quality as well as values of performance parameter.

Keywords

MRI Non-local averaging Gaussian noise Method noise 

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Copyright information

© Springer India 2015

Authors and Affiliations

  • Aditya Srivastava
    • 1
  • Vikrant Bhateja
    • 1
  • Harshit Tiwari
    • 1
  • S. C. Satapathy
    • 2
  1. 1.Department of Electronics and Communication EngineeringShri Ramswaroop Memorial Group of Professional CollegesLucknowIndia
  2. 2.Department of Computer ScienceANITSVishakhapatnamIndia

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