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Unsupervised Change Detection of KOMPSAT-3 Satellite Imagery Based on Cross-sharpened Images by Guided Filter

Guided Filter를 이용한 교차융합영상 기반 KOMPSAT-3 위성영상의 무감독변화탐지

  • Choi, Jaewan (School of Civil Engineering, Chungbuk National University) ;
  • Park, Honglyun (Department of Civil Engineering, Chungbuk National University) ;
  • Kim, Donghak (Department of Civil Engineering, Chungbuk National University) ;
  • Choi, Seokkeun (School of Civil Engineering, Chungbuk National University)
  • 최재완 (충북대학교 토목공학부) ;
  • 박홍련 (충북대학교 토목공학과) ;
  • 김동학 (충북대학교 토목공학과) ;
  • 최석근 (충북대학교 토목공학부)
  • Received : 2018.10.07
  • Accepted : 2018.10.15
  • Published : 2018.10.31

Abstract

GF (Guided Filtering) is a representative image processing technique to effectively remove noise while preserving edge information in the digital image. In this paper, we proposed a unsupervised change detection method for the KOMPSAT-3 satellite image using the GF and evaluated its performance. In order to utilize GF for the unsupervised change detection, cross-sharpened images were generated based on GF, and CVA (Change Vector Analysis) was applied to the generated cross-sharpened images to extract the changed area in the multitemporal satellite imagery. Experimental results using KOMPSAT-3 satellite images showed that the proposed method can be effectively used to detect changed regions compared with CVA results based on existing cross-sharpened images.

Acknowledgement

Grant : 국토위성정보 수집 및 활용기술개발

Supported by : 국토교통부

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