Perceptual Digital Imaging
Computational Photography
Single-Sensor Imaging
Color Image Processing
Super-Resolution Imaging
Cultural Heritage Imaging
Visual Cryptography
Graphs: Theory & Practice
Image Restoration


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


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


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

Locally adaptive processing methods versus globally optimal methods


Modern techniques for motion estimation


How to integrate robustness


Bayesian statistical approaches


Learning-based methods


Applications in remote sensing and medicine


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.


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


Provides detailed coverage of implementations and applications


Contains numerous examples, illustrations, tables and figures


Explores new digital image and video processing applications


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

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

Home | Perceptual Digital Imaging | Computational Photography | Single-Sensor Imaging | Color Image Processing | Super-Resolution Imaging | Cultural Heritage Imaging | Visual Cryptography | Graphs: Theory & Practice | Image Restoration

Last update: 03/20/11

2006 Rastislav Lukac