Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
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Switching Filter using Distribution of Histogram in Salt and Pepper Noise Environments

Salt and Pepper 잡음 환경에서 히스토그램의 분포를 이용한 스위칭 필터

  • Baek, Ji-Hyeon (Dept. of Smart Robot Convergence and Application Engineering, Pukyong National University) ;
  • Park, Jun-Mo (School of Electronic and Biomedical Engineering, Tongmyong University) ;
  • Kim, Nam-Ho (Dept. of Control and Instrumentation Engineering, Pukyong National University)
  • 백지현 (부경대학교 스마트로봇융합응용공학과) ;
  • 박준모 (동명대학교 전자및의용공학부) ;
  • 김남호 (부경대학교 제어계측공학과)
  • Received : 2020.06.12
  • Accepted : 2020.09.25
  • Published : 2020.09.30
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Abstract

With the recent development of communication equipment, the demand for communication equipment is gradually increasing. Accordingly, various signal processing has been studied. In the case of an image, noise removal is an indispensable step because noise propagation problems may occur if noise is not removed in the pre-processing process. Salt and Pepper noise is a typical impulse noise with two extremes. Various studies have been conducted to remove such noise, and there are CWMF, MF and MMF. However, the existing methods are somewhat insufficient in the high-density noise region. Therefore, in this study, we have proposed an algorithm that filters the size of the mask according to the number of noises inside the 7×7 mask and filters it with a modified switching filter using the histogram distribution of the image. In the case of the proposed algorithm, noise can be effectively removed in a high-density noise region. For objective judgment, PSNR was used to compare and analyze with existing algorithms.

최근 통신장비가 발달함에 따라 통신장비의 수요가 점차 늘어나고 있는 추세이다. 이에 따라 다양한 신호 처리가 연구되어져 왔다. 그 중 영상은 전처리 과정에서 잡음을 제거하지 않으면 오류의 전파라는 문제를 야기할 수 있기 때문에 잡음 제거가 필수불가결한 단계이다. Salt and Pepper 잡음의 경우 두 개의 극값을 가지는 대표적인 임펄스 잡음이다. 이러한 잡음을 제거하기 위해 다양한 연구가 진행되어 왔으며 CWMF, MF, MMF 등이 있다. 하지만 기존의 방법들은 고밀도 잡음 영역에서 다소 미흡한 모습을 보인다. 따라서 본 연구에서는 7×7 마스크 내부의 잡음개수에 따라 마스크의 크기를 다르게 하고, 영상의 히스토그램 분포를 이용하여 변형된 스위칭 필터로 필터링하는 알고리즘을 제안하였다. 제안한 알고리즘의 경우 고밀도 잡음 영역에서 효과적으로 잡음을 제거할 수 있으며, 객관적인 판단을 위해 PSNR을 이용하여 기존의 알고리즘들과 비교, 분석하였다.

Keywords

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