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Estimation of subpixel target size for remotely sensed imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 42 n° 6 (June 2004)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 42 n° 6 (June 2004) . - pp 1309 - 1320 Titre : Estimation of subpixel target size for remotely sensed imagery Type de document : Article/Communication Auteurs : C.I. Chang, Auteur ; H. Ren, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 1309 - 1320 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse infrapixellaire [Termes IGN] analyse linéaire des mélanges spectraux [Termes IGN] estimation statistique [Termes IGN] identification automatique [Termes IGN] méthode des moindres carrés Résumé : (Auteur) One of the challenges in remote sensing image processing is subpixel detection where the target size is smaller than the ground sampling distance, therefore, embedded in a single pixel. Under such a circumstance, these targets can be only detected spectrally at the subpixel level, not spatially as ordinarily conducted by classical image processing techniques. This paper investigates a more challenging issue than subpixel detection, which is the estimation of target size at the subpixel level. More specifically, when a subpixel target is detected, we would like to know "what is the size of this particular target within the pixel?" The proposed approach is to estimate the abundance fraction of a subpixel target present in a pixel, then find what portion it contributes to the pixel that can be used to determine the size of the subpixel target by multiplying the ground sampling distance. In order to make our idea work, the subpixel target abundance fraction must be accurately estimated to truly reflect the portion of a subpixel target occupied within a pixel. So, a fully constrained linear unmixing method is required to reliably estimate the abundance fractions of a subpixel target for its size estimation. In this paper, a recently developed fully constrained least squares linear unmixing is used for this purpose. Experiments are conducted to demonstrate the utility of the proposed method in comparison with an unconstrained linear unmixing method, onconstrained least squares method, two partially constrained last square linear unmixing methods, sum-to-one constrained least squares, and nonnegativity constrained least squares. Numéro de notice : A2004-263 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2004.826559 En ligne : https://doi.org/10.1109/TGRS.2004.826559 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26790 [article]

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