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Motion Deblurring : Algorithms and Systems / edited by A. N. Rajagopalan, Rama Chellappa.

Contributor(s): Publisher: Cambridge : Cambridge University Press, 2014Description: 1 online resource (306 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781107360181 (ebook)
Additional physical formats: Print version: : No titleDDC classification:
  • 006.6 23
LOC classification:
  • TA1637.5 .M68 2014
Online resources: Summary: 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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Title from publisher's bibliographic system (viewed on 07 Mar 2017).

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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