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

  • 제25권10호
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  • Pages.1317-1322
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  • 2021
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  • 2234-4772(pISSN)
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  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
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영상 잡음 제거를 위한 반복적 저 계수 근사

Iterative Low Rank Approximation for Image Denoising

  • Kim, Seehyun (Department of Information and Communications Engineering, The University of Suwon)
  • 투고 : 2021.09.27
  • 심사 : 2021.10.07
  • 발행 : 2021.10.31
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초록

영상 신호에는 비지역적 유사성이 존재하므로 임의의 조각 영상 즉, 패치(patch)에 대해 유사한 패치들을 모아 구성한 패치행렬은 낮은 계수값(rank)을 갖는 특성이 있다. 백색 잡음이 섞인 영상으로 구성된 패치행렬은 원 영상에 비해 높은 계수값을 갖게 된다. 이 행렬에 대해 저 계수의 근사 행렬을 구하면 영상 속의 잡음을 제거할 수 있다. 본 논문에서는 기준 패치의 유사 패치들을 이용한 패치행렬 구성 방법과 패치행렬에 대한 저 계수 행렬 근사 방법 및 이를 이용한 영상 복원 방법으로 구성된 영상 잡음 제거 방식을 제안한다. 또한 모의실험을 통해 제안된 방식의 잡음 제거 성능을 최신 4가지 방법들과 비교하여 그 우수성을 보인다.

Nonlocal similarity of natural images leads to the fact that a patch matrix whose columns are similar patches of the reference patch has a low rank. Images corrupted by additive white Gaussian noises (AWGN) make their patch matrices to have a higher rank. The noise in the image can be reduced by obtaining low rank approximation of the patch matrices. In this paper, an image denoising algorithm is proposed, which first constructs the patch matrices by combining the similar patches of each reference patch, which is a part of the noisy image. For each patch matrix, the proposed algorithm calculates its low rank approximate, and then recovers the original image by aggregating the low rank estimates. The simulation results using widely accepted test images show that the proposed denoising algorithm outperforms four recent methods.

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참고문헌

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