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전처리한 픽셀을 이용한 Salt and Pepper 잡음 제거

Salt and Pepper Noise Removal using Processed Pixels

  • Baek, Ji-Hyeon (Dept. of Control and Instrumentation Eng., Pukyong National University) ;
  • Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyong National University)
  • 투고 : 2019.06.11
  • 심사 : 2019.07.06
  • 발행 : 2019.09.30

초록

최근 IT 기술이 발전함에 따라서 디스플레이 등 영상장치들에 대한 수요가 갈수록 높아지고 있다. 그러나 영상 데이터를 전송하는 과정에서 다양한 이유로 잡음이 발생하고 주로 Salt and Pepper noise가 대표적이다. 이러한 잡음을 제거하는 대표적인 방법으로는 A-TMF, CWMF, AMF 등이 있고, 고밀도 잡음 영역에서 잡음 제거 성능이 다소 미흡하게 나타난다. 따라서 본 논문에서는 고밀도 잡음 환경에서 효과적으로 잡음 처리를 하기 위해, 잡음 유무를 판단하여 비잡음인 경우 원 화소를 대치하고 잡음인 경우 $3{\times}3$의 국부마스크를 처리한 요소의 영역과 처리할 요소의 영역으로 구분한다. 그리고 각 요소마다 다르게 가중치를 적용하여 평균필터로 처리하는 알고리즘을 제안하였다. 성능 판단을 위해서 PSNR을 이용하여 기존의 Salt and Pepper noise의 제거 방법들과 비교하였다.

In response to the recent development of IT technologies, there are more demands for visual devices such as display. However, noise is generated in the process of sending video data due to various reasons. Noise is the representative noise which is commonly found. While A-TMF, CWMF, and AMF are the typical ways for removing Salt and Pepper noise, the noise is not removed well in high-density noise environment. To remove the noise in the high-density noise environment, this study suggested an algorithm which identifies whether it's noise or not. If it's not a noise, matches the original pixel. If it's a noise, divide the $3{\times}3$ local mask into the area of the element treated and the area of the element to be processed. Then, algorithm proposes to apply different weights for each element to treat it as an average filter. To analyze the performance of the algorithm, this study compared PSNR to compare the algorithm with other existing methods.

키워드

참고문헌

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