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Object-based Change Detection using Various Pixel-based Change Detection Results and Registration Noise

다양한 화소기반 변화탐지 결과와 등록오차를 이용한 객체기반 변화탐지

  • Jung, Se Jung (Department of Geospatial Information, Kyungpook National University) ;
  • Kim, Tae Heon (Department of Geospatial Information, Kyungpook National University) ;
  • Lee, Won Hee (School of Geospatial Information, Kyungpook National University) ;
  • Han, You Kyung (School of Geospatial Information, Kyungpook National University)
  • Received : 2019.11.19
  • Accepted : 2019.12.03
  • Published : 2019.12.31

Abstract

Change detection, one of the main applications of multi-temporal satellite images, is an indicator that directly reflects changes in human activity. Change detection can be divided into pixel-based change detection and object-based change detection. Although pixel-based change detection is traditional method which is mostly used because of its simple algorithms and relatively easy quantitative analysis, applying this method in VHR (Very High Resolution) images cause misdetection or noise. Because of this, pixel-based change detection is less utilized in VHR images. In addition, the sensor of acquisition or geographical characteristics bring registration noise even if co-registration is conducted. Registration noise is a barrier that reduces accuracy when extracting spatial information for utilizing VHR images. In this study object-based change detection of VHR images was performed considering registration noise. In this case, object-based change detection results were derived considering various pixel-based change detection methods, and the major voting technique was applied in the process with segmentation image. The final object-based change detection result applied by the proposed method was compared its performance with other results through reference data.

다시기 위성 영상을 이용한 변화탐지 분석은 인간 활동의 변화를 직접 반영하는 지표이다. 변화탐지는 크게 화소 기반 변화탐지(PBCD: Pixel-Based Change Detection)와 객체 기반 변화탐지(OBCD: Object-Based Change Detection)로 구분한다. 화소 기반 변화탐지는 알고리즘이 간단하고 비교적 쉽게 정량적 분석이 가능해 전통적으로 많이 쓰여온 기법이나 고해상도 영상에서의 화소 기반 변화탐지는 오탐지나 노이즈(noise)가 발생하기 때문에 고해상도 영상에서의 활용도가 떨어진다. 또한, 고해상도 다시기 영상은 취득 당시 센서의 자세나 지형적 특성으로 인해 영상 등록(image registration)을 수행한 이후에도 지형적 불일치가 발생한다. 등록오차(registration noise)라고 불리는 이 지형 불일치는 고해상도 다시기 영상 활용을 위한 공간정보 추출 시 정확도를 떨어뜨리는 방해요인으로 작용한다. 이에 본 연구에서는 등록오차를 고려한 고해상도 영상의 객체 기반 변화탐지를 수행하였다. 이 때, 다양한 화소 기반 변화탐지 결과를 모두 고려한 객체 기반 변화탐지 결과를 도출하였으며 이 과정에서 분할 영상(segmentation image)과의 major voting을 적용하였다. 제안 기법과 화소 기반 변화탐지 결과, 그리고 화소 기반 변화탐지 결과를 객체 기반 변화탐지로 확장한 결과의 비교를 통해 제안 기법의 우수성을 평가하였다.

Keywords

Acknowledgement

Grant : 국토위성정보 수집 및 활용기술개발

Supported by : 국토교통부

본 연구는 국토교통부 위성정보 활용센터 설립 운영 사업(과제명: 국토위성정보 수집 및 활용기술개발)의 연구비지원(과제번호: 18SIUE-B148326-01)에 의해 수행되었습니다. 본 연구는 한국항공우주연구원의 위성정보활용사업의 지원을 받아 수행되었습니다.

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