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Visual perception is a complex process requiring interaction
between the receptors in the eye that sense the stimulus and the
neural system and the brain that are responsible for communicating
and interpreting the sensed visual information. This process
involves several physical, neural, and cognitive phenomena whose
understanding is essential to design effective and computationally
efficient imaging solutions. Building on advances in computer
vision, image and video processing, neuroscience, and information
engineering, perceptual digital imaging greatly enhances the
capabilities of traditional imaging methods. Filling a gap in the
literature, Perceptual Digital Imaging: Methods and Applications
comprehensively covers the system design, implementation, and
application aspects of this emerging specialized area. It gives
readers a strong, fundamental understanding of theory and methods,
providing a foundation on which solutions for many of the most
interesting and challenging imaging problems can be built. The book
features contributions by renowned experts who present the state of
the art and recent trends in image acquisition, processing,
storage, display, and visual quality evaluation. They detail
advances in the field and explore human visual system-driven
approaches across a broad spectrum of applications, including:
Image quality and aesthetics assessment Digital camera imaging
White balancing and color enhancement Thumbnail generation Image
restoration Super-resolution imaging Digital halftoning and
dithering Color feature extraction Semantic multimedia analysis and
processing Video shot characterization Image and video encryption
Display quality enhancement This is a valuable resource for readers
who want to design and implement more effective solutions for
cutting-edge digital imaging, computer vision, and multimedia
applications. Suitable as a graduate-level textbook or stand-alone
reference for researchers and practitioners, it provides a unique
overview of an important and rapidly developing research field.
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.
Visual perception is a complex process requiring interaction
between the receptors in the eye that sense the stimulus and the
neural system and the brain that are responsible for communicating
and interpreting the sensed visual information. This process
involves several physical, neural, and cognitive phenomena whose
understanding is essential to design effective and computationally
efficient imaging solutions. Building on advances in computer
vision, image and video processing, neuroscience, and information
engineering, perceptual digital imaging greatly enhances the
capabilities of traditional imaging methods. Filling a gap in the
literature, Perceptual Digital Imaging: Methods and Applications
comprehensively covers the system design, implementation, and
application aspects of this emerging specialized area. It gives
readers a strong, fundamental understanding of theory and methods,
providing a foundation on which solutions for many of the most
interesting and challenging imaging problems can be built. The book
features contributions by renowned experts who present the state of
the art and recent trends in image acquisition, processing,
storage, display, and visual quality evaluation. They detail
advances in the field and explore human visual system-driven
approaches across a broad spectrum of applications, including:
Image quality and aesthetics assessment Digital camera imaging
White balancing and color enhancement Thumbnail generation Image
restoration Super-resolution imaging Digital halftoning and
dithering Color feature extraction Semantic multimedia analysis and
processing Video shot characterization Image and video encryption
Display quality enhancement This is a valuable resource for readers
who want to design and implement more effective solutions for
cutting-edge digital imaging, computer vision, and multimedia
applications. Suitable as a graduate-level textbook or stand-alone
reference for researchers and practitioners, it provides a unique
overview of an important and rapidly developing research field.
Color Image Processing: Methods and Applications embraces two
decades of extraordinary growth in the technologies and
applications for color image processing. The book offers
comprehensive coverage of state-of-the-art systems, processing
techniques, and emerging applications of digital color imaging. To
elucidate the significant progress in specialized areas, the
editors invited renowned authorities to address specific research
challenges and recent trends in their area of expertise. The book
begins by focusing on color fundamentals, including color
management, gamut mapping, and color constancy. The remaining
chapters detail the latest techniques and approaches to
contemporary and traditional color image processing and analysis
for a broad spectrum of sophisticated applications, including:
Vector and semantic processing Secure imaging Object recognition
and feature detection Facial and retinal image analysis Digital
camera image processing Spectral and superresolution imaging Image
and video colorization Virtual restoration of artwork Video shot
segmentation and surveillance Color Image Processing: Methods and
Applications is a versatile resource that can be used as a graduate
textbook or as stand-alone reference for the design and the
implementation of various image and video processing tasks for
cutting-edge applications. This book is part of the Digital Imaging
and Computer Vision series.
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