Multi-sensor imagery rectification and registration for herbicide testing

被引:4
|
作者
Aguera-Vega, Francisco [1 ,2 ]
Aguera-Puntas, Marta [1 ,2 ]
Aguera-Vega, Juan [3 ,4 ]
Martinez-Carricondo, Patricio [1 ,2 ]
Carvajal-Ramirez, Fernando [1 ,2 ]
机构
[1] Univ Almeria, Dept Ingn, Almeria, Spain
[2] Campus Excelencia Int Agroalimentaria ceiA3, Ctr Invest Mediterraneo Econ & Desarrollo Sosteni, Almeria, Spain
[3] Univ Cordoba, Dept Ingn Rural, Cordoba, Spain
[4] Campus Excelencia Int Agroalimentaria CeiA3, Almeria, Spain
关键词
Image registration; Multispectral images; Thermal images;
D O I
10.1016/j.measurement.2021.109049
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The use of multi-spectral sensors has been focused on several agricultural tasks, yet it is necessary to further assess this approach to achieve sufficient precision to carry out adequately these. Metric information from these images is traditionally derived by photogrammetric techniques, but with a major limitation: photographed objects should be static while the photographs are being taken, but plants are generally in movement because of wind and this causes the photogrammetric process to be unable to generate the necessary information to make any metric measurement. To bypass this, metric information can be derived via rectification, using only one photograph. This work aims to develop a band co-registration method with agricultural purposes, based on rectified images taken from different sensors usually mounted on UAVs or terrestrial vehicles, studying its accuracy in a quantitative way. All multispectral information co-registered in a precise way will allow the calculation or development of new radiometric and even geometric indices that will help to improve efficiency in many tasks related to agriculture. Images taken from a multi-spectral (green, near infra-red, red and red edge) and a thermal camera were used to apply the developed methodology. First, a digital elevation model describing the displacement produced by distortion due to the sensor lens was obtained and applied to each of the studied pictures to correct this distortion. Then, distortion due to conic perspective present in the photographs was corrected, taking into account the homology relationship between the photographed object and the picture. To carry out these tasks, several computers programs were developed. Subsequently, the edges of the five bands corresponding to 250 plants were digitalised and their areas were measured. Furthermore, the intersection of the five bands of each plant was calculated, and an index (AI) indicating the fraction of the area of each band, which was out of the common area edge of the five bands, was calculated for each plant. The average value of this index for each band ranged from 0.22 to 0.24, with no statistically significant differences between them, indicating a high accuracy of the proposed methodology.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Automatic registration of multi-sensor airborne imagery
    Fan, Xiaofeng
    Rhody, Harvey
    Saber, Eli
    34TH APPLIED IMAGERY AND PATTERN RECOGNITION WORKSHOP: MULTI-MODAL IMAGING, 2006, : 81 - +
  • [2] Multi-sensor registration of earth remotely sensed imagery
    Le Moigne, J
    Cole-Rhodes, A
    Eastman, R
    Johnson, K
    Morisette, J
    Netanyahu, NS
    Stone, HS
    Zavorin, I
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING VII, 2002, 4541 : 1 - 10
  • [3] A new multi-sensor registration
    Li, Mei
    Sivananthan, Siva
    Sittler, Robert
    2006 IEEE RADAR CONFERENCE, VOLS 1 AND 2, 2006, : 788 - +
  • [4] Registration in a distributed multi-sensor environment
    Parkinson, GC
    Xue, DP
    Farooq, M
    40TH MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1 AND 2, 1998, : 993 - 996
  • [5] Fusion of noisy multi-sensor imagery
    Mishra, Anima
    Rakshit, Subrata
    DEFENCE SCIENCE JOURNAL, 2008, 58 (01) : 136 - 146
  • [6] Stereo-based registration of multi-sensor imagery for enhanced visualization of remote environments
    Elstrom, MD
    Smith, PW
    ICRA '99: IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-4, PROCEEDINGS, 1999, : 1948 - 1953
  • [7] Multi-sensor imagery cueing (MUSIC)
    Rodvold, DM
    Patterson, TJ
    SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION XI, 2002, 4729 : 144 - 151
  • [8] A verification metric for multi-sensor image registration
    DelMarcol, Stephen
    Tom, Victor
    Webb, Helen
    Lefebvre, David
    SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION XVI, 2007, 6567
  • [9] Spatiotemporal Registration for Multi-sensor Fusion Systems
    Bu, Shi-zhe
    Zhou, Gong-jian
    INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTER SCIENCE (AICS 2016), 2016, : 333 - 339
  • [10] SAR geocoding and multi-sensor image registration
    Werner, C
    Strozzi, T
    Wegmüller, U
    Wiesmann, A
    IGARSS 2002: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS: REMOTE SENSING: INTEGRATING OUR VIEW OF THE PLANET, 2002, : 902 - 904