Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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AWGN Removal Algorithm using Similarity Determination of Block Matching

블록 매칭의 유사도 판별을 이용한 AWGN 제거 알고리즘

  • Cheon, Bong-Won (Dept. of Smart Robot Convergence and Application Eng., Pukyong National University) ;
  • Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyong National University)
  • Received : 2020.05.29
  • Accepted : 2020.06.09
  • Published : 2020.11.30
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Abstract

In this paper, we propose an algorithm to remove AWGN by considering the characteristics of noise present in the image. The proposed algorithm uses block matching to calculate the output, and calculates an estimate by determining the similarity between the center mask and the matching mask. The output of the filter is calculated by adding or subtracting the estimated value and the input pixel value, and weighting is given according to the standard deviation of the center mask and the noise constant to obtain the final output. In order to evaluate the proposed algorithm, the simulation was performed in comparison with the existing methods, and analyzed through the enlarged image and PSNR comparison. The proposed algorithm minimizes the effect of noise, preserves important characteristics of the image, and shows the performance of removing noise efficiently.

본 논문에서는 영상에 존재하는 잡음의 특성을 고려하여 AWGN을 제거하기 위한 알고리즘을 제안한다. 제안한 알고리즘은 출력 계산을 위해 블록 매칭을 사용하였으며, 센터 마스크와 매칭 마스크의 유사도 판별하여 추정치를 계산한다. 필터의 출력은 추정치와 입력 화소값을 가감하여 계산하며, 센터 마스크의 표준 편차와 잡음 상수에 따라 가중치를 부여하여 최종 출력을 구한다. 제안하는 알고리즘을 평가하기 위해 기존 방법들과 비교하여 시뮬레이션하였으며, 확대영상 및 PSNR비교를 통해 분석하였다. 제안한 알고리즘은 잡음의 영향을 최소화하였으며, 영상의 중요 특성을 보존하며 효율적으로 잡음을 제거하는 성능을 보였다.

Keywords

References

  1. T. K. Kim, I. H. Song, and S. H. Lee, "Noise Reduction of HDR Detail Layer using a Kalman Filter Adapted to Local Image Activity," Journal of Korea Multimedia Society, vol. 22, no. 1, pp. 10-17, Jan. 2019. https://doi.org/10.9717/KMMS.2019.22.1.010
  2. S. Y. Kim, S. H. Yu, and J. C. Jeong, "Design and Analysis of an Image Restoration using Wiener Filter with a Quality Based Hybrid Algorithms," in Conference on The Institute of Electronics and Information Engineers, Incheon : Korea, pp. 430-433, 2018.
  3. P. S. V. S. Sridhar, R. Caytiles, "Efficient Cloud Data Hosting Availability," Asia-pacific Journal of Convergent Research Interchange, HSST, ISSN : 2508-9080, vol. 3, no. 2, pp. 11-19, Jun. 2017. http://dx.doi.org/10.21742/APJCRI.2017.06.02
  4. S. Y. Kim, S. H. Yu, and J. C. Jeong, "A Wiener Filter Using Edge Detection for Gaussian Noise Reduction," in Conference on The Institute of Electronics and Information Engineers, Incheon : Korea, pp. 430-433, 2018.
  5. K. Chithra and T. Santhanam, "Hybrid Denoising Technique for Suppressing Gaussian Noise in Medical Images," in 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), Chennai : India, pp. 1460-1463, 2017.
  6. B. W. Cheon and N. H. Kim, "Noise Removal Algorithm Considering High Frequency Components in AWGN Environments," Journal of the Korea Institute of Information and Communication Engineerin, vol. 22, no. 6, pp. 867-873, Jun. 2018.
  7. Y. H. Kim and J. H. Nam, "Statistical algorithm and application for the noise variance estimation," Journal of the Korean Data & Information Science Society, vol. 20, no. 5, pp. 869-878, Sep. 2009.