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Research on UAV Remote Sensing Image Mosaic Method Based on SIFT

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJSIP) 바로가기
  • 간행물
    International Journal of Signal Processing, Image Processing and Pattern Recognition 바로가기
  • 통권
    Vol.8 No.11 (2015.11)바로가기
  • 페이지
    pp.365-374
  • 저자
    Yinjiang Jia, Zhongbin Su, Qi Zhang, Yu Zhang, Yunhao Gu, Zhongqiu Chen
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A270025

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원문정보

초록

영어
UAV remote sensing, as a new method of remote sensing, has the characteristics of higher spatial resolution, fine timeliness and high flexibility. It is widely used in the field of natural disaster monitoring, urban planning, resource investigation, and has become one of the indispensable method of remote sensing data acquisition. However, because the UAV remote sensing platform is limited by the flight height and focal length of camera, the acquired image size is smaller, single image can’t cover the entire target area. Therefore, image mosaic has become a key technology to solve the problem. Image matching and image fusion are the key techniques of image mosaic. Due to the good robustness of image scaling, translation and rotation, this paper uses the SIFT algorithm to realize image matching of UAV. Since the feature extraction may produce false matches, RANSAC algorithm is applied to the feature point purification points. According to the seam-line in jointing overlap region, weighted fusion algorithm is applied to realize the image seamless splicing.

목차

Abstract
 1. Introduction
 2. UAV Remote Sensing Image Mosaic Process
  2.1. Image Preprocessing
  2.2. Image Registration
  2.3. Image Fusion
 3. SIFT Algorithm Principle
  3.1. Construction of Scale Space
  3.2. Keypoint detection
  3.3. Determination of the Keypoint
  3.4. Generation of Keypoint Descriptor
 4. The Experimental Environment and Data
 5. The Experimental Results and Analysis
  5.1. Image Read
  5.2. Gaussian Pyramid Build
  5.3. Difference of Gaussian Pyramid Build
  5.4. Feature point extraction
  5.5. Feature point matching
  5.6. Feature Point Purification
  5.7. Image fusion
 6. Conclusions
 References

키워드

UAV image mosaic image registration image fusion SIFT algorithm

저자

  • Yinjiang Jia [ College of Electrical and Information, Northeast Agricultural University, Harbin 150030, China ]
  • Zhongbin Su [ College of Electrical and Information, Northeast Agricultural University, Harbin 150030, China ]
  • Qi Zhang [ College of Electrical and Information, Northeast Agricultural University, Harbin 150030, China ]
  • Yu Zhang [ College of Electrical and Information, Northeast Agricultural University, Harbin 150030, China ]
  • Yunhao Gu [ College of Electrical and Information, Northeast Agricultural University, Harbin 150030, China ]
  • Zhongqiu Chen [ China mobile communication technology engineering company, Harbin 150000, China ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 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

  • 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.8 No.11

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