대한전자공학회논문지SP (Journal of the Institute of Electronics Engineers of Korea SP)

대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지

위성영상에서의 적응적 압축잡음 제거 알고리즘

Content Analysis-based Adaptive Filtering in The Compressed Satellite Images

  • 최태현 (중앙대학교 첨단 영상대학원 영상학과) ;
  • 지정민 (중앙대학교 첨단 영상대학원 영상학과) ;
  • 박준훈 (중앙대학교 첨단 영상대학원 영상학과) ;
  • 최명진 (한국항공우주연구원) ;
  • 이상근 (중앙대학교 첨단 영상대학원 영상학과)
  • Choi, Tae-Hyeon (Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University) ;
  • Ji, Jeong-Min (Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University) ;
  • Park, Joon-Hoon (Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University) ;
  • Choi, Myung-Jin (Korea Aerospace Research Institute) ;
  • Lee, Sang-Keun (Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University)
  • 투고 : 2011.02.14
  • 심사 : 2011.08.17
  • 발행 : 2011.09.25
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초록

본 논문에서는 위성영상을 압축하는 과정에서 발생하는 압축잡음을 내용 분석을 통해 적응적으로 제거하는 디블록킹 알고리즘을 제안 한다. 특히, 제공된 KOMPSAT(korean multi-purpose satellite)-2는 열 단위로 동일한 양자화 계수를 적용하며 고주파 성분이 많은 부분을 압축하여 효율 및 시간을 향상 시켰으나 압축률이 높은 동일 열 내에 복잡도가 낮은 부분에서 압축 잡음이 나타나는 문제점이 있다. 이러한 압축잡음을 제거하기 위해 일반적인 디블록킹 필터를 적용 시 복잡한 영역을 평활화시키는 문제점이 있다. 따라서 제안한 방법에서는 영상 분석 후 적응적 디블록킹 필터를 통해 에지를 보존하면서 격자잡음을 제거 한다. 이와 동시에 WLFPCA(weighted lowpass filter using principle component analysis)를 이용하여 큰 곡선형 경계부분의 계단잡음을 제거 하였다. 제안한 방법은 성능을 평가하기 위한 모의실험 결과로부터 기존의 방법에 비하여 객관적 화질 지표인 PSNR(peak signal to noise ratio)과 주관적 화질 지표인 MSSIM(mean structural similarity)에서 비슷하거나 향상된 결과를 보였으며 특히, 기존의 압축잡음 제거 알고리즘은 반복적 프로세싱을 통해 계단잡음을 제거하나 제안한 방법은 싱글패스(single-path) 방식으로 시간을 크게 단축시켜 실시간에 가까운 처리가 가능하도록 하였으며, 계산양을 줄여 하드웨어의 적용이 용이하게 하였다.

In this paper, we present a deblocking algorithm that removes grid and staircase noises, which are called "blocking artifacts", occurred in the compressed satellite images. Particularly, the given satellite images are compressed with equal quantization coefficients in row according to region complexity, and more complicated regions are compressed more. However, this approach has a problem that relatively less complicated regions within the same row of complicated regions have blocking artifacts. Removing these artifacts with a general deblocking algorithm can blur complex and undesired regions as well. Additionally, the general filter lacks in preserving the curved edges. Therefore, the proposed algorithm presents an adaptive filtering scheme for removing blocking artifacts while preserving the image details including curved edges using the given quantization step size and content analysis. Particularly, WLFPCA (weighted lowpass filter using principle component analysis) is employed to reduce the artifacts around edges. Experimental results showed that the proposed method outperforms SA-DCT in terms of subjective image quality.

키워드

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