Cluster Computing

, Volume 22, Supplement 6, pp 14495–14504 | Cite as

Patch based fast noise level estimation using DCT and standard deviation

  • S. B. MohanEmail author
  • T. A. Raghavendiran
  • R. Rajavel


Image noise level estimation play a vital role in image processing applications such as medical imaging and celestial imaging. The noise level estimation of image is hard to estimate due to texture of image. Conventional methods segment image in blocks to identify noise in image. The method provides erroneous noise detection in high textured image such as medical images. In this paper, we propose a Patch based DCT (PDCT) model to decompose image in spatial domain in parallel pool loop for medical image slices. The PDCT model split noisy image into patches to exhibit noise in image. The PDCT model estimates noise level accurately in complex images compared to conventional noise level estimation methods such as principle component analysis and weak textured patch methods.


Noise level estimation DCT White Gaussian noise Average estimation error Image denoising 



This research was supported by Chase Technologies. We thank Mr. A. Vignesh and Mr. E. Ganesh who provide insight and expertise that greatly assisted this research.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • S. B. Mohan
    • 1
    Email author
  • T. A. Raghavendiran
    • 2
  • R. Rajavel
    • 3
  1. 1.Department of Electronics and Communication EngineeringDhaanish Ahmed College of EngineeringChennaiIndia
  2. 2.Department of Electrical and Electronics EngineeringAnand Institute of Higher TechnologyChennaiIndia
  3. 3.Department of Electronics and Communication EngineeringSSN College of EngineeringChennaiIndia

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