Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Modified Gaussian Filter based on Fuzzy Membership Function for AWGN Removal in Digital Images

  • Cheon, Bong-Won (Department of Smart Robot Convergence and Application Engineering, Pukyong National University) ;
  • Kim, Nam-Ho (Department of Control and Instrumentation Engineering, Pukyong National University)
  • Received : 2020.11.17
  • Accepted : 2021.03.16
  • Published : 2021.03.31
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Abstract

Various digital devices were supplied throughout the Fourth Industrial Revolution. Accordingly, the importance of data processing has increased. Data processing significantly affects equipment reliability. Thus, the importance of data processing has increased, and various studies have been conducted on this topic. This study proposes a modified Gaussian filter algorithm based on a fuzzy membership function. The proposed algorithm calculates the Gaussian filter weight considering the standard deviation of the filtering mask and computes an estimate according to the fuzzy membership function. The final output is calculated by adding or subtracting the Gaussian filter output and estimate. To evaluate the proposed algorithm, simulations were conducted using existing additive white Gaussian noise removal algorithms. The proposed algorithm was then analyzed by comparing the peak signal-to-noise ratio and differential image. The simulation results show that the proposed algorithm has superior noise reduction performance and improved performance compared to the existing method.

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References

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