방송공학회논문지 (Journal of Broadcast Engineering)

  • 제16권1호
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  • Pages.14-22
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  • 2011
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  • 1226-7953(pISSN)
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  • 2287-9137(eISSN)
한국방송∙미디어공학회 (The Korean Institute of Broadcast and Media Engineers)
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다중분광 영상의 색상별 스펙트럼 영역을 고려한 웨이블릿 변역 IKONOS 위성영상 융합 알고리즘

A Wavelet-Domain IKONOS Satellite Image Fusion Algorithm Considering the Spectrum Range of Multispectral Images

  • 이영건 (공군사관학교 전자전산학과) ;
  • 국중갑 (서울대학교 전기컴퓨터공학부) ;
  • 조남익 (서울대학교 전기컴퓨터공학부)
  • Lee, Young-Gun (Dept. of Electrical Engineering and Computer Science, Korea Air Force Academy) ;
  • Kuk, Jung-Gap (Dept. of Electrical and Computer Engineering, Seoul National Univ.) ;
  • Cho, Nam-Ik (Dept. of Electrical and Computer Engineering, Seoul National Univ.)
  • 투고 : 2010.07.19
  • 심사 : 2011.01.06
  • 발행 : 2011.01.30
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초록

기존의 대표적인 위성영상 융합방법들의 경우 해상도가 높은 팬크로매틱 영상에서 얻은 고주파수 성분을 모든 저해상도의 다중분광 영상 (Color성분/IR성분 등)마다 똑같이 더함으로써 고화질의 컬러 위성영상을 합성하였다. 그러나 다중분광영상들의 스펙트럼을 살펴보면 각 채널마다 대역폭이 서로 다르고 평균적인 밝기도 서로 다르므로 기존의 방법에서와 같이 각 성분에 동일한 고주파 성분을 더하면 일부 다중분광영상이 왜곡되어 전체적인 컬러가 왜곡되는 현상이 나타난다. 따라서 본 논문에서는 이러한 밝기와 스펙트럼 중첩의 차이를 보상하는 새로운 웨이블릿 변역 위성영상합성 알고리즘을 제안한다. 구체적으로, 각 다중분광영상의 밝기차이를 보정하기 위하여 서로의 명암비를 고려하면서 팬크로매틱 영상으로부터 각 채널의 고해상도 영상을 합성하는 방법을 제안한다. 그리고 다중분광 영상들 사이의 대역폭 차이를 보정하기 위한 방안으로서 각각의 웨이블릿 계수를 구하여 이들을 웨이블릿 변역에서 대역폭에 비례한 상수를 곱해서 고주파 성분을 더해주는 방법을 제시하였다. 실험은 스펙트럼의 특성이 잘 알려진 IKONOS 위성영상에 대하여 수행하였으며, 실험 결과 제안하는 알고리즘이 PSNR과 상관도 평가에서 기존의 방법보다 더 좋다는 것을 확인하였다.

The conventional satellite image fusion methods usually add the same amount of higher frequency components extracted from the panchromatic image to all the multispectral images. However, it is noted that each of multispectral images has different amount of overlap with the panchromatic image in terms of its spectrum, and also has different intensities. Thus giving the same amount of high frequency contents to all the spectral bands does not match with this observation, which causes color distortion in the fused image. In this paper, we propose a new wavelet-domain satellite image fusion algorithm that can compensate for these differences in intensity and spectrum overlap. For the compensation of intensity differences, we first estimate the high resolution multispectral images from P, considering the relative intensity ratios. For the compensation of the amount of spectral overlap, their wavelet coefficients are appended to the conventional wavelet-domain method where the coefficients for the addition is determined by the amount of spectrum overlap. Experiments are conducted for the IKONOS satellite images whose spectrums are well known, and the results show that the proposed algorithm gives higher PSNR and correlation coefficients compared to the conventional methods.

키워드

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