Motion Deblurring
Algorithms and Systems

Comprehensive guide to the restoration of images degraded by motion blur, encompassing algorithms and architectures, with novel computational photography methods.

A. N. Rajagopalan (Edited by), Rama Chellappa (Edited by)

9781107044364, Cambridge University Press

Hardback, published 8 May 2014

306 pages, 150 b/w illus. 4 tables
25.5 x 17.8 x 2 cm, 0.79 kg

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.

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.

Subject Areas: Image processing [UYT], Signal processing [UYS], Computer vision [UYQV]