Introduction to Image Processing Using R: Learning by Examples: SpringerBriefs in Computer Science
Autor Alejandro C. Frery, Talita Percianoen Limba Engleză Paperback – 7 feb 2013
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Specificații
ISBN-13: 9781447149491
ISBN-10: 1447149491
Pagini: 104
Ilustrații: XV, 87 p. 42 illus., 17 illus. in color.
Dimensiuni: 155 x 235 x 5 mm
Greutate: 0.16 kg
Ediția:2013
Editura: SPRINGER LONDON
Colecția Springer
Seria SpringerBriefs in Computer Science
Locul publicării:London, United Kingdom
ISBN-10: 1447149491
Pagini: 104
Ilustrații: XV, 87 p. 42 illus., 17 illus. in color.
Dimensiuni: 155 x 235 x 5 mm
Greutate: 0.16 kg
Ediția:2013
Editura: SPRINGER LONDON
Colecția Springer
Seria SpringerBriefs in Computer Science
Locul publicării:London, United Kingdom
Public țintă
ResearchCuprins
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.
Recenzii
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)
“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)
Textul de pe ultima copertă
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.
Caracteristici
This book introduces the statistical software R in an intuitive and practical manner Presents and explains both the theory and practice of R code concepts and techniques Encourages the reader to try their own implementations to develop faster, optimized programs Includes supplementary material: sn.pub/extras