Computational photography refers broadly to imaging techniques that
enhance or extend the capabilities of digital photography. This new
and rapidly developing research field has evolved from computer
vision, image processing, computer graphics and applied optics-and
numerous commercial products capitalizing on its principles have
already appeared in diverse market applications, due to the gradual
migration of computational algorithms from computers to imaging
devices and software. Computational Photography: Methods and
Applications provides a strong, fundamental understanding of theory
and methods, and a foundation upon which to build solutions for
many of today's most interesting and challenging computational
imaging problems. Elucidating cutting-edge advances and
applications in digital imaging, camera image processing, and
computational photography, with a focus on related research
challenges, this book: Describes single capture image fusion
technology for consumer digital cameras Discusses the steps in a
camera image processing pipeline, such as visual data compression,
color correction and enhancement, denoising, demosaicking,
super-resolution reconstruction, deblurring, and high dynamic range
imaging Covers shadow detection for surveillance applications,
camera-driven document rectification, bilateral filtering and its
applications, and painterly rendering of digital images Presents
machine-learning methods for automatic image colorization and
digital face beautification Explores light field acquisition and
processing, space-time light field rendering, and dynamic view
synthesis with an array of cameras Because of the urgent challenges
associated with emerging digital camera applications, image
processing methods for computational photography are of paramount
importance to research and development in the imaging community.
Presenting the work of leading experts, and edited by a renowned
authority in digital color imaging and camera image processing,
this book considers the rapid developments in this area and
addresses very particular research and application problems. It is
ideal as a stand-alone professional reference for design and
implementation of digital image and video processing tasks, and it
can also be used to support graduate courses in computer vision,
digital imaging, visual data processing, and computer graphics,
among others.
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