De-noising of an Image using Fuzzy Inference System and Performance Comparison with the Conventional system

Authors

  • Ahmed Farhan College of Information and Communication Engineering, Harbin Engineering University, Heilongjiang, China
  • Rezwan us Saleheen Department of Mechatronics Engineering, World University of Bangladesh, Dhaka, Bangladesh
  • Chen Li Wei College of Information and Communication Engineering, Harbin Engineering University, Heilongjiang, China
  • Farhan Mahbub Department of Mechatronics Engineering, World University of Bangladesh, Dhaka, Bangladesh

DOI:

https://doi.org/10.38032/jea.2021.03.007

Keywords:

Fuzzy Logic, Fuzzy Inference System, Salt & Pepper Noise, PSNR, MSE

Abstract

Noise prevailing in the image can diminish the physical appearance of the objects existing within the image and make them frail. Present research emphasizes a fuzzy inference system eradicating several types of noise from the images. The investigation implies the utilization of different levels of Salt & Pepper noise. Followed by the pixel determination applying a mask, the disparity between the focused pixel's intensity with the minimum, average, and maximum power of the chosen window has been determined. Since two fuzzy valued outputs have been obtained to match them, the one provided by a low noise rate would demonstrate the more accurate filter for the selected window. Utilizing Matlab the Peak Signal-to-Noise ratio (PSNR) and Mean Square Error (MSE) are determined for evaluating the noise reduction performance. However, these values of PSNR and MSE obtained from this research are also compared with the conventional fuzzy filtering system.

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Published

04-09-2021
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How to Cite

Farhan, A. ., Saleheen, R. us, Wei, C. L. ., & Mahbub, F. . (2021). De-noising of an Image using Fuzzy Inference System and Performance Comparison with the Conventional system. Journal of Engineering Advancements, 2(03), 164–168. https://doi.org/10.38032/jea.2021.03.007

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Research Articles