@Article{ZanottaHaerShimRenn:2014:LiSpMi,
               author = "Zanotta, Daniel Capella and Haertel, Vitor and Shimabukuro, Yosio 
                         Edemir and Renn{\'o}, Camilo Daleles",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and Center for 
                         Remote Sensing, Federal University at Rio Grande do Sul, Porto 
                         Alegre, Brazil and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Linear spectral mixing model for identifying potential missing 
                         endmembers in spectral mixture analysis",
              journal = "IEEE Transactions on Geoscience and Remote Sensing",
                 year = "2014",
               volume = "52",
               number = "5",
                pages = "3005--3012",
             keywords = "endmember extraction, residual term, spectral mixture analysis, 
                         uncertainty.",
             abstract = "A problem that is frequently arising in the spectral mixture 
                         analysis is how to correctly identify the endmembers present in 
                         the scene. In the analysis of image data covering natural scenes, 
                         vegetation, bare soil, and shade/water are commonly assumed as 
                         endmembers, but other endmembers may also be present. This paper 
                         investigates an approach based on the analysis of residuals 
                         produced by the linear spectral mixing model for identifying 
                         potential missing endmembers. The basic proposition consists in 
                         assuming that larger residuals are caused by missing endmembers. 
                         The image is segmented in terms of the residuals, and the 
                         KolmogorovSmirnov test is applied to group segments that show 
                         similar residuals and are thus likely to include the same missing 
                         endmember. An approach to estimate the spectral response of the 
                         missing endmembers is also investigated. The proposed methodology 
                         is tested by using Thematic Mapper Landsat and Coupled Charge 
                         Device ChinaBrazil Earth Resources Satellite image data. In 
                         addition to vegetation, bare soil, and shade/water, two additional 
                         endmembers were included as missing endmembers (clouds and water 
                         bodies with a large load of suspended sediments). The tests have 
                         shown that the proposed methodology is capable of detecting image 
                         regions that include missing endmembers and of correctly 
                         estimating the corresponding spectral responses.",
                  doi = "10.1109/TGRS.2013.2268539",
                  url = "http://dx.doi.org/10.1109/TGRS.2013.2268539",
                 issn = "0196-2892",
                label = "self-archiving-INPE-MCTI-GOV-BR",
             language = "en",
        urlaccessdate = "30 abr. 2024"
}