This is an introductory to intermediate level text on the science
of image processing, which employs the Matlab programming language
to illustrate some of the elementary, key concepts in modern image
processing and pattern recognition. The approach taken is
essentially practical and the book offers a framework within which
the concepts can be understood by a series of well chosen examples,
exercises and computer experiments, drawing on specific examples
from within science, medicine and engineering.
Clearly divided into eleven distinct chapters, the book begins
with a fast-start introduction to image processing to
enhance the accessibility of later topics. Subsequent chapters
offer increasingly advanced discussion of topics involving more
challenging concepts, with the final chapter looking at
the application of automated image classification (with Matlab
examples) .
Matlab is frequently used in the book as a tool for
demonstrations, conducting experiments and for solving problems, as
it is both ideally suited to this role and is widely available.
Prior experience of Matlab is not required and those without access
to Matlab can still benefit from the independent presentation of
topics and numerous examples.
* Features a companion website href=’http://www.wiley.com/go/solomon/fundamentals’>www.wiley.com/go/solomon/fundamentals
containing a Matlab name=’_Go Back’>fast-start primer, further
exercises, examples, instructor resources and accessibility to all
files corresponding to the examples and exercises within the book
itself.
* Includes numerous examples, graded exercises and computer
experiments to support both students and instructors alike.
关于作者
Dr Chris Solomon, Applied Optics Group, School of Physical Sciences, The University of Kent, Canterbury, Kent, UK.
Dr Stuart Gibson, Vision Metric, Canterbury, Kent, UK.
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