@InProceedings{LiuHe:2012:AuAlRe,
               author = "Liu, Huichan and He, Guojin",
                title = "Auto-Matching Algorithm for Remote Sensing Images",
            booktitle = "Proceedings...",
                 year = "2012",
               editor = "Feitosa, Raul Queiroz and Costa, Gilson Alexandre Ostwald Pedro da 
                         and Almeida, Cl{\'a}udia Maria de and Fonseca, Leila Maria Garcia 
                         and Kux, Hermann Johann Heinrich",
                pages = "248--251",
         organization = "International Conference on Geographic Object-Based Image 
                         Analysis, 4. (GEOBIA).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Landsat-TM Image, Remote Sensing, Image Matching, Feature 
                         Matching.",
             abstract = "Image registration is the process of overlaying two or more images 
                         of the same scene taken at different times, from different 
                         viewpoints, and/or by different sensors. The present differences 
                         between images are introduced due to different imaging conditions. 
                         As image registration geometrically aligns two imagesthe reference 
                         and non-corrected images, it becomes a crucial step in all image 
                         analysis tasks. Image registration is mainly divided into three 
                         steps: first is to choose matching points between the noncorrected 
                         image and the reference image, second is to determine the 
                         parameters and type of the mapping function with these matching 
                         points, third is to use mapping function to transform the 
                         non-corrected image. Among them, the selection of matching points 
                         usually adopts artificially selection manner whose efficiency is 
                         quite low. This paper will combine Harris algorithm, 
                         standardization cross-correlation algorithm, and least mean square 
                         algorithm to automatically match the Landsat-TM images. This 
                         method can produce matching points with high precision, and 
                         without manual work it also saves a lot of time.",
  conference-location = "Rio de Janeiro",
      conference-year = "May 7-9, 2012",
                 isbn = "978-85-17-00059-1",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP8W/3BTFF32",
                  url = "http://urlib.net/ibi/8JMKD3MGP8W/3BTFF32",
           targetfile = "071.pdf",
                 type = "Segmentation",
        urlaccessdate = "21 maio 2024"
}