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Compression of Terrain Data using Integer Wavelet Transform (IWT) and Application on Gravity Terrain Correction

정수웨이블릿변환(IWT)을 이용한 지형 자료의 압축 및 정밀 지형 효과 계산을 위한 활용 방법 고찰

  • Chung, Hojoon (Human and Earth) ;
  • Lee, Heuisoon (Human and Earth) ;
  • Oh, Seokhoon (Department of Energy and Resources Engineering, Kangwon National University) ;
  • Park, Gyesoon (Mineral Resources Research Division, Korea Institute of Geoscience and Mineral Resources) ;
  • Rim, Hyoungrea (Mineral Resources Research Division, Korea Institute of Geoscience and Mineral Resources)
  • 정호준 ((주)휴먼앤어스) ;
  • 이희순 ((주)휴먼앤어스) ;
  • 오석훈 (강원대학교 에너지자원공학과) ;
  • 박계순 (한국지질자원연구원 광물자원연구본부) ;
  • 임형래 (한국지질자원연구원 광물자원연구본부)
  • Received : 2013.01.17
  • Accepted : 2013.02.01
  • Published : 2013.02.28

Abstract

Terrain data is one of important basic data in various areas of Earth science. Recently, finer DEM data is available, which necessary to develop a method that deals with such huge data efficiently. This study was conducted on the lossless compression of DEM data and efficient partial reconstruction of terrain information from compressed data. In this study, we compressed the wavelet coefficients of DEM, obtained from integer wavelet transform (IWT) by entropy encoding. CDF (Cohen-Daubechies-Feauveau) 3.5 wavelet showed the best compression ratio of about 45.4% and the optimum decomposition level was 3. Results also showed that a small region of terrain could be restored from the inverse wavelet transform with a part of the wavelet coefficients that are related to such region instead of whole reconstruction. We discussed the potential applications of the terrain data compression for precise gravity terrain correction.

지형 자료는 지구과학 여러 분야에서 중요한 기초 자료 중 하나이다. 최근 들어, 상세한 분해능을 가지는 DEM 자료가 활용가능하며 따라서 방대한 양의 자료를 효율적으로 다루는 방법이 필요하다. 본 연구에서는 방대한 DEM 자료의 무손실 압축 및 효율적인 복원에 대해 알아보았다. 이를 위해 정수웨이블릿 변환과, 엔트로피 부호화의 개념을 이용하여, 웨이블릿 계수의 부호화 및 일부 영역의 지형복원 방법을 고안하였다. 또한, 정밀 중력 지형보정 과정에서 이러한 연구 결과의 활용성을 검토하였다. DEM의 압축률이 가장 좋은 웨이블릿은 CDF3.5이며, CDF3.1 또는 CDF3.5 웨이블릿을 사용하여 3단계 정도로 분해를 하는 것이 최적의 선택이다 (약 45.4%의 압축률). 또한 웨이블릿변환의 다중단계분석 특성을 활용하여 웨이블릿계수의 일부만을 추출하여 지형의 일부만을 복원할 수 있었다.

Keywords

References

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