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    1. Data och IT
    2. Systemvetenskap och AI

    Introduction to Image Processing Using R

    Learning by Examples

    AvAlejandro C. Frery,Talita Perciano

    Häftad, Engelska, 2013

    Del i serien SpringerBriefs in Computer Science

    615 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    This book introduces the statistical software R to the image processing community in an intuitive and practical manner. R brings interesting statistical and graphical tools which are important and necessary for image processing techniques. Furthermore, it has been proved in the literature that R is among the most reliable, accurate and portable statistical software available. Both the theory and practice of R code concepts and techniques are presented and explained, and the reader is encouraged to try their own implementation to develop faster, optimized programs. Those who are new to the field of image processing and to R software will find this work a useful introduction. By reading the book alongside an active R session, the reader will experience an exciting journey of learning and programming.

    Produktinformation

    • Utgivningsdatum:2013-02-07
    • Mått:155 x 235 x 7 mm
    • Vikt:172 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:SpringerBriefs in Computer Science
    • Antal sidor:87
    • Upplaga:2013
    • Förlag:Springer London Ltd
    • ISBN:9781447149491

    Utforska kategorier

    • Systemvetenskap och AI inom Data och IT
    • Programmeringsböcker inom Data och IT

    Recensioner i media

    From the reviews: "This book addresses the basic use of R for image processing ... . The index is well designed and the presentation of the subject is adequate, given the short length of the chapters. Both professionals and students in image processing or statistical data analysis could use this book as a good guide to using R for image processing." (G. Albeanu, Computing Reviews, July, 2013)

    Innehållsförteckning

    • Definitions and Notation.- Image Data Formats and Color Representation.- Reading and Writing Images with R: Generating High Quality Output.- Contrast Manipulation.- Filters in the Image Domain.- Contrast Enhancement and Dimensionality Reduction by Principal.
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