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A new book on Super-Resolution Imaging published!

Explore new techniques and applications of super-resolution imaging!

A volume in the Digital Imaging and Computer Vision series

Super-Resolution Imaging

Edited by:
Peyman Milanfar
University of California, Santa Cruz, California, USA

Boca Raton, FL, CRC Press / Taylor & Francis, September 2010
ISBN 978-1-4398-1930-2

Audience:
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Academic community (graduate student, post-doc and faculty) in Electrical Engineering, Computer Science, and Applied Mathematics

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Industrial community (engineers, engineering managers, research lab staff and managers)

 

With the exponential increase in computing power and broad proliferation of digital cameras, super-resolution imaging is poised to become the next "killer app." The growing interest in this technology has manifested itself in an explosion of literature on the subject. Super-Resolution Imaging consolidates key recent research contributions from eminent scholars and practitioners in this area and serves as a starting point for exploration into the state of the art in the field. It describes the latest in both theoretical and practical aspects of direct relevance to academia and industry, providing a base of understanding for future progress.

Recent advances in camera sensor technology have led to an increasingly larger number of pixels being crammed into ever-smaller spaces. This has resulted in an overall decline in the visual quality of recorded content, necessitating improvement of images through the use of post-processing. Providing a snapshot of the cutting edge in super-resolution imaging, this book focuses on methods and techniques to improve images and video beyond the capabilities of the sensors that acquired them. It covers:

bulletHistory and future directions of super-resolution imaging
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Locally adaptive processing methods versus globally optimal methods

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Modern techniques for motion estimation

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How to integrate robustness

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Bayesian statistical approaches

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Learning-based methods

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Applications in remote sensing and medicine

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Practical implementations and commercial products based on super-resolution

The book concludes by concentrating on multidisciplinary applications of super-resolution for a variety of fields. It covers a wide range of super-resolution imaging implementation techniques, including variational, feature-based, multi-channel, learning-based, locally adaptive, and nonparametric methods. This versatile book can be used as the basis for short courses for engineers and scientists, or as part of graduate-level courses in image processing.

    Features:
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Presents a comprehensive overview of the field, surveying the latest techniques in super-resolution imaging

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Provides detailed coverage of implementations and applications

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Contains numerous examples, illustrations, tables and figures

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Explores new digital image and video processing applications

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Features top contributors from USA, UK, Israel, Japan, and the European Union

Additional material is available at the companion web site www.colorimageprocessing.org.

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Last update: 03/20/11

2006 Rastislav Lukac