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Image Processing and Acquisition using Python (Hardcover, 2nd edition)
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Image Processing and Acquisition using Python (Hardcover, 2nd edition)
Series: Chapman & Hall/CRC The Python Series
Expected to ship within 12 - 17 working days
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Image Processing and Acquisition using Python provides readers with
a sound foundation in both image acquisition and image
processing-one of the first books to integrate these topics
together. By improving readers' knowledge of image acquisition
techniques and corresponding image processing, the book will help
them perform experiments more effectively and cost efficiently as
well as analyze and measure more accurately. Long recognized as one
of the easiest languages for non-programmers to learn, Python is
used in a variety of practical examples. A refresher for more
experienced readers, the first part of the book presents an
introduction to Python, Python modules, reading and writing images
using Python, and an introduction to images. The second part
discusses the basics of image processing, including pre/post
processing using filters, segmentation, morphological operations,
and measurements. The second part describes image acquisition using
various modalities, such as x-ray, CT, MRI, light microscopy, and
electron microscopy. These modalities encompass most of the common
image acquisition methods currently used by researchers in academia
and industry. Features Covers both the physical methods of
obtaining images and the analytical processing methods required to
understand the science behind the images. Contains many examples,
detailed derivations, and working Python examples of the
techniques. Offers practical tips on image acquisition and
processing. Includes numerous exercises to test the reader's skills
in Python programming and image processing, with solutions to
selected problems, example programs, and images available on the
book's web page. New to this edition Machine learning has become an
indispensable part of image processing and computer vision, so in
this new edition two new chapters are included: one on neural
networks and the other on convolutional neural networks. A new
chapter on affine transform and many new algorithms. Updated Python
code aligned to the latest version of modules.
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