The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Adaptive Noise Detection and Removal Algorithm Using Local Statistics and Noise Estimation

국부 통계 특성 및 노이즈 예측을 통한 적응 노이즈 검출 및 제거 방식

  • 응웬 뚜안안 (숭실대학교 정보통신전자공학부) ;
  • 김범수 (숭실대학교 정보통신전자공학부) ;
  • 홍민철 (숭실대학교 정보통신전자공학부)
  • Received : 2013.01.11
  • Accepted : 2013.02.15
  • Published : 2013.02.28
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Abstract

In this paper, we propose a spatially adaptive noise detection and removal algorithm for a single degraded image. Under the assumption that an observed image is Gaussian-distributed, the noise information is estimated by local statistics of degraded image, and the degree of the additive noise is detected by the local statistics of the estimated noise. In addition, we describe a noise removal method taking a modified Gaussian filter which is adaptively determined by filter parameters and window size. The experimental results demonstrate the capability of the proposed algorithm.

본 논문에서는 첨부 노이즈에 의해 훼손된 왜곡 영상의 공간 적응적 노이즈 검출 및 제거 기법에 대해 제안한다. 일반적인 영상이 가우시안 분포 특성을 갖는다는 가정 하에 왜곡 영상으로부터 국부 통계 특성을 산출하여 첨부 노이즈 정보를 예측하고, 예측된 노이즈 정보의 통계 특성을 활용하여 첨부 노이즈 정도를 분류하는 기법에 대해 제안한다. 더불어, 노이즈 분류에 따라 보정된 가우시안 필터의 매개변수 및 필터 윈도우 크기를 설정한 적응 노이즈 필터 기법에 대해 기술한다. 실험 결과를 통해 제안 방식의 성능이 기존 방식과 비교하여 객관적, 주관적으로 우수한 능력을 갖고 있음을 확인할 수 있었다.

Keywords

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