Motion Deblurring (eBook, ePUB)

Algorithms and Systems
Redaktion: Rajagopalan, A. N.

• Format: ePub

Produktbeschreibung

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.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 8. Mai 2014
• Englisch
• ISBN-13: 9781139949415
• Artikelnr.: 41072876

Inhaltsangabe

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.