To achieve the complex task of interpreting what we see, our
brains rely on statistical regularities and patterns in visual
data. Knowledge of these regularities can also be considerably
useful in visual computing disciplines, such as computer vision,
computer graphics, and image processing. The field of natural image
statistics studies the regularities to exploit their potential and
better understand human vision. With numerous color figures
throughout, Image Statistics in Visual Computing covers all aspects
of natural image statistics, from data collection to analysis to
applications in computer graphics, computational photography, image
processing, and art.
The authors keep the material accessible, providing mathematical
definitions where appropriate to help readers understand the
transforms that highlight statistical regularities present in
images. The book also describes patterns that arise once the images
are transformed and gives examples of applications that have
successfully used statistical regularities. Numerous references
enable readers to easily look up more information about a specific
concept or application. A supporting website also offers additional
information, including descriptions of various image databases
suitable for statistics.
Collecting state-of-the-art, interdisciplinary knowledge in one
source, this book explores the relation of natural image statistics
to human vision and shows how natural image statistics can be
applied to visual computing. It encourages readers in both academic
and industrial settings to develop novel insights and applications
in all disciplines that relate to visual computing.
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