@InProceedings{CastejonForsFonsMarc:2009:AvMéCa,
               author = "Castejon, Emiliano Ferreira and Forster, Carlos Henrique Quartucci 
                         and Fonseca, Leila Maria Garcia and Marcari Junior, Etore",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais - INPE} and {Instituto 
                         Tecnol{\'o}gico da Aeron{\'a}utica - ITA} and {Instituto 
                         Nacional de Pesquisas Espaciais - INPE} and {Instituto Nacional de 
                         Pesquisas Espaciais - INPE}",
                title = "Avalia{\c{c}}{\~a}o de m{\'e}todos de casamento de imagens para 
                         mosaico de imagens orbitais",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "6805--6812",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 14. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "CBERS image, remote sensing, image processing, register, mosaic, 
                         sensoriamento remoto, processamento de imagens, registro, 
                         mosaico.",
             abstract = "The increasing number of satellite images has reinforced the need 
                         for automatic image mosaicking and registration methods. Several 
                         techniques for automatic image registration have been developed - 
                         Fonseca and Manjunath et al (1996); Zitov{\'a} and Flusser 
                         (2003). One of the phases in the registration and mosaicking 
                         processes is the image matching that uses similarity measures to 
                         identify control points in the images. Similarity measures such as 
                         correlation, means squared difference and morphological have been 
                         used to register remote sensing images. However, these measures 
                         are more adequate to register images with similar spectral 
                         responses. Some authors have proposed the use of a metric based on 
                         mutual information to register images acquired in different time 
                         and different sensor. In order to evaluate some similarity 
                         measures, this paper describes a comparative study and a practical 
                         evaluation of three matching metrics based on: Correlation, Mutual 
                         Information (MI) and Scale Invariant Feature Transform (SIFT). 
                         Real situations problems such as the registration of temporal, 
                         spectral and cloud coverage images are analyzed and tested. The 
                         results showed that the method based on MI got the best 
                         performance in spite of its high computational cost.",
  conference-location = "Natal",
      conference-year = "25-30 abr. 2009",
                 isbn = "978-85-17-00044-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2008/11.15.21.41",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.15.21.41",
           targetfile = "6805-6812.pdf",
                 type = "Processamento de Imagens",
        urlaccessdate = "02 maio 2024"
}