Unscented blind image de-blurring using camera with inertial measurement unit

Chin Yuan Tseng*, Jian An Chen, Jwu-Sheng Hu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Image blur resulting from camera motion is an annoying factor for robotic vision, especially for high-speed applications. This work proposes a sensor fusion model for blind image de-blurring using inertial measurement unit. The model attempts to observe the camera motion, estimate the point spread function and de-convolute the image simultaneously. To solve the problem, an iterative estimation procedure using Maximum A-Posteriori Expectation-Maximization (MAP-EM) algorithms and Unscented Kalman Filter are proposed. Simulation results show the feasibility of the proposed formulation to blindly de-blurring the image under camera motion.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest
Pages2096-2101
Number of pages6
DOIs
StatePublished - 1 Dec 2012
Event2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Guangzhou, China
Duration: 11 Dec 201214 Dec 2012

Publication series

Name2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest

Conference

Conference2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012
CountryChina
CityGuangzhou
Period11/12/1214/12/12

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