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Elastic Image Registration for Landslides Monitoring
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- 발행기관
- 보안공학연구지원센터(IJSIP) 바로가기
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- 간행물
- International Journal of Signal Processing, Image Processing and Pattern Recognition 바로가기
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- 통권
- vol.3 no.3 (2010.09)바로가기
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- 페이지
- pp.71-86
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A148410
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Landslide is a type of mass movement that causes damage in many areas. The evolving remote sensing technology in producing high resolution images may help in landslide studies. However, the problem in detecting small size landslides is still challenging when suitable image resolution of the area being analyzed is not available. In this paper, a novel method based on elastic image registration, appropriate for the detection of small landslides will be presented. This method can be used to detect and quantify landslide movement with sub-pixel accuracy. It is based on the invocation of deformation operators which imitate the deformations expected to be observed when a landslide occurs. The similarity between two images is measured by a similarity function which takes into consideration grey level value correlation and geometric deformation. The geometric deformation term ensures that the minimum necessary deformation compatible with the two images is employed. An extra term, ensuring maximum overlap between the two images is also incorporated. There are two versions of this method. One using the correlation coefficient as a measure of similarity for the grey level value, and another one using mutual information. These methods are tested using known small scale landslides images of southern Italy taken from the Landsat 5 TM. The mutual information-based method gives more reliable results.
목차
Abstract
1. Introduction
2. Methodology
2.1. Exponential growth operator
2.2. Exponential shrinkage operator
2.3. Exponential translation operator
2.4. Exponential parabolic flow front operator
3. Imagery used
4. Choice of parameter values
4.1. Parameters of the operators
4.2. Stopping criterion
4.3. Parameter β and λ
5. Results and discussion
6. Conclusions
7. References
키워드
Mathematical models; Deformation operators; Elastic image registration; Correlation coefficient; Mutual information; Landslide monitoring저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
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- 간행물명
- International Journal of Signal Processing, Image Processing and Pattern Recognition
- 간기
- 격월간
- pISSN
- 2005-4254
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition vol.3 no.3
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