Isbn: 9780387940281 - minimax theory of image reconstruction: 82 (10 risultati)

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  • Lingua: Inglese

    Editore: Springer, 1993

    0387940286 / 9780387940281

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer, 1993

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    Condizione: New. pp. 276.

  • Lingua: Inglese

    Editore: Springer Verlag, 1993

    0387940286 / 9780387940281

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    Paperback. Condizione: Brand New. 1st edition. 270 pages. 9.25x6.10x0.63 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, Springer, 1993

    0387940286 / 9780387940281

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - There exists a large variety of image reconstruction methods proposed by different authors (see e. g. Pratt (1978), Rosenfeld and Kak (1982), Marr (1982)). Selection of an appropriate method for a specific problem in image analysis has been always considered as an art. How to find the image reconstruction method which is optimal in some sense In this book we give an answer to this question using the asymptotic minimax approach in the spirit of Ibragimov and Khasminskii (1980a,b, 1981, 1982), Bretagnolle and Huber (1979), Stone (1980, 1982). We assume that the image belongs to a certain functional class and we find the image estimators that achieve the best order of accuracy for the worst images in the class. This concept of optimality is rather rough since only the order of accuracy is optimized. However, it is useful for comparing various image reconstruction methods. For example, we show that some popular methods such as simple linewise processing and linear estimation are not optimal for images with sharp edges. Note that discontinuity of images is an important specific feature appearing in most practical situations where one has to distinguish between the 'image domain' and the 'background' . The approach of this book is based on generalization of nonparametric regression and nonparametric change-point techniques. We discuss these two basic problems in Chapter 1. Chapter 2 is devoted to minimax lower bounds for arbitrary estimators in general statistical models.

  • Lingua: Inglese

    Editore: Springer, 1993

    0387940286 / 9780387940281

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    Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books

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  • Lingua: Inglese

    Editore: Springer New York Apr 1993, 1993

    0387940286 / 9780387940281

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -There exists a large variety of image reconstruction methods proposed by different authors (see e. g. Pratt (1978), Rosenfeld and Kak (1982), Marr (1982)). Selection of an appropriate method for a specific problem in image analysis has been always considered as an art. How to find the image reconstruction method which is optimal in some sense In this book we give an answer to this question using the asymptotic minimax approach in the spirit of Ibragimov and Khasminskii (1980a,b, 1981, 1982), Bretagnolle and Huber (1979), Stone (1980, 1982). We assume that the image belongs to a certain functional class and we find the image estimators that achieve the best order of accuracy for the worst images in the class. This concept of optimality is rather rough since only the order of accuracy is optimized. However, it is useful for comparing various image reconstruction methods. For example, we show that some popular methods such as simple linewise processing and linear estimation are not optimal for images with sharp edges. Note that discontinuity of images is an important specific feature appearing in most practical situations where one has to distinguish between the 'image domain' and the 'background' . The approach of this book is based on generalization of nonparametric regression and nonparametric change-point techniques. We discuss these two basic problems in Chapter 1. Chapter 2 is devoted to minimax lower bounds for arbitrary estimators in general statistical models. 276 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer New York, 1993

    0387940286 / 9780387940281

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    Da: moluna, Greven, Germaniamoluna

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    Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. There exists a large variety of image reconstruction methods proposed by different authors (see e. g. Pratt (1978), Rosenfeld and Kak (1982), Marr (1982)). Selection of an appropriate method for a specific problem in image analysis has been always considere.

  • Lingua: Inglese

    Editore: Springer, 1993

    0387940286 / 9780387940281

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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    Condizione: New. Print on Demand pp. 276 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

  • Lingua: Inglese

    Editore: Springer, 1993

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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    Condizione: New. PRINT ON DEMAND pp. 276.

  • Lingua: Inglese

    Editore: Springer, Springer Apr 1993, 1993

    0387940286 / 9780387940281

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -There exists a large variety of image reconstruction methods proposed by different authors (see e. g. Pratt (1978), Rosenfeld and Kak (1982), Marr (1982)). Selection of an appropriate method for a specific problem in image analysis has been always considered as an art. How to find the image reconstruction method which is optimal in some sense In this book we give an answer to this question using the asymptotic minimax approach in the spirit of Ibragimov and Khasminskii (1980a,b, 1981, 1982), Bretagnolle and Huber (1979), Stone (1980, 1982). We assume that the image belongs to a certain functional class and we find the image estimators that achieve the best order of accuracy for the worst images in the class. This concept of optimality is rather rough since only the order of accuracy is optimized. However, it is useful for comparing various image reconstruction methods. For example, we show that some popular methods such as simple linewise processing and linear estimation are not optimal for images with sharp edges. Note that discontinuity of images is an important specific feature appearing in most practical situations where one has to distinguish between the 'image domain' and the 'background' . The approach of this book is based on generalization of nonparametric regression and nonparametric change-point techniques. We discuss these two basic problems in Chapter 1. Chapter 2 is devoted to minimax lower bounds for arbitrary estimators in general statistical models.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 276 pp. Englisch.