Motion Deblurring

A comprehensive guide to restoring images degraded by motion blur, bridging the traditional approaches and emerging computational photography-based techniques, and bringing together a wide range of methods emerging from basic theory as well as cutting-edge research. It encompasses both algorithms and architectures, providing detailed coverage of practical techniques by leading researchers. From an algorithms perspective, blind and non-blind approaches are discussed, including the use of single or multiple images; projective motion blur model; image priors and parametric models; high dynamic range imaging in the irradiance domain; and image recognition in blur. Performance limits for motion deblurring cameras are also presented. From a systems perspective, hybrid frameworks combining low-resolution-high-speed and high-resolution-low-speed cameras are described, along with the use of inertial sensors and coded exposure cameras. Also covered is an architecture exploiting compressive sensing for video recovery. A valuable resource for researchers and practitioners in computer vision, image processing, and related fields.

Features novel methods based on computational photography
Includes algorithms as well as systems for motion deblurring
Provides comprehensive coverage of a wide array of topics in motion blur, serving as one-stop resource for any reader interested in motion blur
Covers basics as well as most recent advances, being suitable both as a textbook and as an advanced compendium on motion blur at graduate level

Product details

Published: June 2014
Format: Adobe eBook Reader
ISBN: 9781139950466
Length: 0 pages
Weight: 0kg
Contains: 150 b/w illus. 4 tables
Availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.

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Contents

1. Mathematical models and practical solvers for uniform motion deblurring Jiaya Jia
2. Spatially varying image deblurring Neel Joshi, Sing Bing Kang and Richard Szeliski
3. Hybrid-imaging for motion deblurring Moshe Ben-Ezra, Yu-Wing Tai, Michael Brown and Shree Nayar
4. Removing camera shake in smart phones without hardware stabilization Filip Sroubek and Jan Flusser
5. Richardson–Lucy deblurring for scenes under a projective motion path Yu-Wing Tai and Michael Brown
6. Multi-sensor fusion for motion deblurring Jingyi Yu
7. Flutter-shutter cameras for motion deblurring Amit Agrawal
8. Efficient, blind, spatially-variant deblurring for shaken images Oliver Whyte, Josef Sivic, Andrew Zisserman and Jean Ponce
9. Coded-exposure motion deblurring for recognition Scott McCloskey
10. HDR imaging in the presence of motion blur C. S. Vijay, C. Paramanand and A. N. Rajagopalan
11. Compressive video sensing to tackle motion blur Ashok Veeraraghavan
12. Direct recognition of motion blurred faces Kaushik Mitra, Priyanka Vageeswaran and Rama Chellappa
13. Performance limits for motion deblurring cameras Olliver Cossairt and Mohit Gupta.

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Contributors

Jiaya Jia, Neel Joshi, Sing Bing Kang, Richard Szeliski, Moshe Ben-Ezra, Yu-Wing Tai, Michael Brown, Shree Nayar, Filip Sroubek, Jan Flusser, Jingyi Yu, Amit Agrawal, Oliver Whyte, Josef Sivic, Andrew Zisserman, Jean Ponce, Scott McCloskey, C. S. Vijay, C. Paramanand, A. N. Rajagopalan, Ashok Veeraraghavan, Kaushik Mitra, Priyanka Vageeswaran, Rama Chellappa, Olliver Cossairt, Mohit Gupta

Editors

A. N. Rajagopalan , Indian Institute of Technology, Madras
A. N. Rajagopalan is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology, Madras. He co-authored the book Depth from Defocus: A Real Aperture Imaging Approach in 1998. He was Alexander von Humboldt Fellow in the Technical University of Munich in 2007–8, is a Fellow of the Indian National Academy of Engineering and a Senior Member of the IEEE. He also received the Outstanding Investigator Award from the Department of Atomic Energy, India in 2012.
Rama Chellappa , University of Maryland, College Park
Rama Chellappa is Minta Martin Professor of Engineering and an affiliate Professor of Computer Science at University of Maryland, College Park. He is also affiliated with the Center for Automation Research and UMIACS, and is serving as the Chair of the ECE department. He is a recipient of the K. S. Fu Prize from the IAPR and the Society, Technical Achievement and Meritorious Service Awards from the IEEE Signal Processing Society. He also received the Technical Achievement and Meritorious Service Awards from the IEEE Computer Society. In 2010, he was recognized as an Outstanding ECE by Purdue University. He is a Fellow of the IEEE, IAPR, OSA and AAAS, a Golden Core Member of the IEEE Computer Society, and has served as a Distinguished Lecturer of the IEEE Signal Processing Society as well as the President of the IEEE Biometrics Council.

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