The Efficacy of the Mean Filter on the Noise Reduction of Digitalized Images

Authors

  • Manne Chowdappa Ramanna Department of Mathematics, SJC Institute of Technology, Chickballapur-562101, Karnataka, India
  • Udaya Kumara Kodipalya Nanjappa Department of Mathematics, School of Applied Sciences, REVA University, Bengaluru, Karnataka, India
  • Sreenivasa Reddy Perla Department of Mathematics, SJC Institute of Technology, Chickballapur-562101, Karnataka, India
  • Kurugal Munikempanna Nagaraja Department of Mathematics, JSS Academy of Technical Education, Uttarahalli-Kengeri Main Road, Bengaluru-560 060, Karnataka, India
  • Sampathkumar Ramachandraiah Department of Mathematics, R N S Institute of Technology, Bengaluru, India
  • Venkataramana B. Siddappa Department of Mathematics, KS Institute of Technology, Bengaluru, India
Volume: 15 | Issue: 4 | Pages: 24291-24297 | August 2025 | https://doi.org/10.48084/etasr.10809

Abstract

Digital Image Processing (DIP) involves the use of a digital computer to process images, where noise introduced during transmission is reduced using suitable filters. Noise reduction is crucial as image quality directly affects result accuracy. This study explores various filters on common images with different types of noise. The Power Exponential Mean (PEM) filter shows strong correlation performance on the Hilbert-curve image with consistent parameters. The results indicate that PEM filters are robust, outperforming other spatial mean filters. PEM maintains performance even with changing image resolution, proving its reliability. It also preserves image structure, luminosity, and granularity, even at large kernel sizes. Many filters degrade at larger kernel sizes, but PEM retains image information. The quantitative evaluation utilized MSE, PSNR, CoC, and MAE, with MATLAB 14b for assessment.

Keywords:

PSNR, MSE, CoC, MAE, noise, mean filters

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How to Cite

[1]
M. C. Ramanna, U. K. K. Nanjappa, S. Reddy Perla, K. M. Nagaraja, S. Ramachandraiah, and V. B. Siddappa, “The Efficacy of the Mean Filter on the Noise Reduction of Digitalized Images”, Eng. Technol. Appl. Sci. Res., vol. 15, no. 4, pp. 24291–24297, Aug. 2025.

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