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  • Analysis of Variance in Statistical Image Processing

    Analysis of Variance in Statistical Image Processing by Kurz, Ludwik; Benteftifa, M. Hafed;

      • GET 20% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice GBP 130.00
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        65 793 Ft (62 660 Ft + 5% VAT)
      • Discount 20% (cc. 13 159 Ft off)
      • Discounted price 52 634 Ft (50 128 Ft + 5% VAT)

    65 793 Ft

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    Availability

    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Cambridge University Press
    • Date of Publication 13 April 1997

    • ISBN 9780521581820
    • Binding Hardback
    • No. of pages226 pages
    • Size 260x185x13 mm
    • Weight 635 g
    • Language English
    • Illustrations 81 b/w illus. 5 tables
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    Short description:

    A detailed account of the techniques and applications of analysis of variance techniques in statistical image processing.

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    Long description:

    A key problem in practical image processing is that of detecting certain features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. A number of computationally efficient algorithms and techniques are then presented, to deal with such problems as line, edge and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

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    Table of Contents:

    Preface; 1. Introduction; 2. Statistical linear models; 3. Line detection; 4. Edge detection; 5. Object detection; 6. Image segmentation; 7. Radial masks in line and edge detection; 8. Performance analysis; 9. Some approaches to image restoration; References; Index.

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