Journal of the Institute of Electronics and Information Engineers (전자공학회논문지)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Effective Noise Reduction using STFT-based Content Analysis

STFT 기반 영상분석을 이용한 효과적인 잡음제거 알고리즘

  • Baek, Seungin (Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University) ;
  • Jeong, Soowoong (Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University) ;
  • Choi, Jong-Soo (Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University) ;
  • Lee, Sangkeun (Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University)
  • 백승인 (중앙대학교 첨단영상대학원 영상학과) ;
  • 정수웅 (중앙대학교 첨단영상대학원 영상학과) ;
  • 최종수 (중앙대학교 첨단영상대학원 영상학과) ;
  • 이상근 (중앙대학교 첨단영상대학원 영상학과)
  • Received : 2014.11.14
  • Accepted : 2015.04.01
  • Published : 2015.04.25
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Abstract

Noise reduction has been actively studied in the digital image processing and recently, block-based denoising algorithms are widely used. In particular, a low rank approximation employing WNNM(Weighted Nuclear Norm Minimization) and block-based approaches demonstrated the potential for effective noise reduction. However, the algorithm based on low rank a approximation generates the artifacts in the image restoration step. In this paper, we analyzes the image content using the STFT(Short Time Fourier Transform) and proposes an effective method of minimizing the artifacts generated from the conventional algorithm. To evaluate the performance of the proposed scheme, we use the test images containing a wide range of noise levels and compare the results with the state-of-art algorithms.

디지털 영상 처리 분야에서 잡음 제거는 활발히 연구되어오고 있으며, 최근에는 블록 기반의 잡음 제거 알고리즘이 널리 사용되고 있다. 저계수행렬 근사 기반의 잡음 제거 알고리즘은 WNNM(Weighted Nuclear Norm Minimization)과 블록 기반의 잡음 제거 방법을 적용하여 잡음 제거 방법에 대한 잠재력을 입증했다. 그러나 저계수행렬 근사 기반의 잡음 제거 알고리즘은 영상복원 과정에서 의도치 않은 아티팩트를 발생시킨다. 본 논문에서는 STFT(Short Time Fourier Transform)을 이용해 영상을 분석하여 기존 알고리즘에서 발생하는 아티팩트를 적응적으로 최소화시키는 방법을 제안한다. 성능을 확인하기 위해 다양한 잡음정도를 포함하는 영상에서 실험하였으며, 비교를 통해 제안된 방법이 기존의 잡음 제거 알고리즘보다 효과적으로 잡음을 제거하는 것을 확인했다.

Keywords

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