Modified Gaussian Filter Considering Noise Characteristics in AWGN Environments

AWGN 환경에서 잡음 특성을 고려한 변형된 가우시안 필터

  • Cheon, Bong-Won (Dept. of Control and Instrumentation Eng., Pukyong National University) ;
  • Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyong National University)
  • 천봉원 (부경대학교 제어계측공학과) ;
  • 김남호 (부경대학교 제어계측공학과)
  • Received : 2019.09.18
  • Accepted : 2019.09.30
  • Published : 2019.09.30

Abstract

Through the 4th Industrial Revolution, various digital equipments are being distributed, and accordingly, the importance of data processing is increasing. As data processing has a great effect on the reliability of equipment, its importance is increasing, and various studies are being conducted. In this paper, we propose an algorithm to remove AWGN in consideration of the noise in the image. The proposed algorithm is used in the filtering process by inferring the standard deviation of the image noise. The noise is removed by dividing the filter for the high frequency component and the filter for the low frequency component compared with the standard deviation of the filtering mask. The proposed algorithm is simulated with the existing methods for evaluation and compared and analyzed by difference image, PSNR and profile. The proposed algorithm minimizes the effect of noise and preserves the important characteristics of the image and shows the performance of efficient noise removal.

4차 산업혁명을 통해 다양한 디지털 장비가 보급되고 있으며, 이에 따라 데이터 처리의 중요성이 높아지고 있다. 데이터 처리는 장비의 신뢰성에 큰 영향을 미치는 만큼 그 중요성이 증가하고 있으며, 다양한 연구가 진행되고 있다. 본 논문에서는 영상에 존재하는 잡음의 특성을 고려하여 AWGN을 제거하기 위한 알고리즘을 제안하였다. 제안한 알고리즘은 영상의 잡음 표준편차를 유추하여 필터링 과정에 사용하였으며, 필터링 마스크의 표준편차와 비교해 고주파 성분에 대한 필터와 저주파 성분에 대한 필터를 구분하여 잡음을 제거하였다. 제안하는 알고리즘을 평가를 위해 기존 방법들과 시뮬레이션하였으며, 차영상 및 PSNR과 프로파일을 통해 비교 분석하였다. 제안한 알고리즘은 잡음의 영향을 최소화하였으며, 영상의 중요 특성을 보존하며 효율적으로 잡음을 제거하는 성능을 보였다.

Keywords

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