LCD Motion Blur: Modeling, Analysis, and Algorithm

Liquid crystal display (LCD) devices are well known for their slow responses due to the physical limitations of liquid crystals. Therefore, fast moving objects in a scene are often perceived as blurred. This effect is known as the LCD motion blur. In order to reduce LCD motion blur, an accurate LCD...

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Veröffentlicht in:IEEE transactions on image processing Jg. 20; H. 8; S. 2352 - 2365
Hauptverfasser: Chan, S. H., Nguyen, T. Q.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.08.2011
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Applied sciences
Cathode ray tubes
Detection, estimation, filtering, equalization, prediction
Devices
Equations
Errors
Exact sciences and technology
Filtering
Human visual system
Humans
Image processing
Image Processing, Computer-Assisted - methods
Information, signal and communications theory
Least-Squares Analysis
Liquid crystal displays
liquid crystal displays (LCDs)
Liquid Crystals
Mathematical model
Mathematical models
Models, Theoretical
Motion
motion blur
Pixel
PSNR
Reduction
Signal and communications theory
Signal processing
Signal, noise
spatial consistency
Studies
subgradient projection
Telecommunications and information theory
temporal consistency
Tracking
Visual Perception
State of the art
Moving target
Video signal
Liquid crystals
Modeling
Projection method
temporal consistency
Reverse filtering
Image sequence
spatial consistency
Motion compensation
motion blur
Target tracking
Least squares problem
L1 approximation
Image restoration
Human visual system
Algorithm
Blurred image
Deconvolution
Algorithm performance
Signal processing
liquid crystal displays (LCDs)
Numerical simulation
Liquid crystal displays
Motion analysis
Signal to noise ratio
subgradient projection
ISSN:1057-7149, 1941-0042, 1941-0042
Online-Zugang:Volltext
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Zusammenfassung:Liquid crystal display (LCD) devices are well known for their slow responses due to the physical limitations of liquid crystals. Therefore, fast moving objects in a scene are often perceived as blurred. This effect is known as the LCD motion blur. In order to reduce LCD motion blur, an accurate LCD model and an efficient deblurring algorithm are needed. However, existing LCD motion blur models are insufficient to reflect the limitation of human-eye-tracking system. Also, the spatiotemporal equivalence in LCD motion blur models has not been proven directly in the discrete 2-D spatial domain, although it is widely used. There are three main contributions of this paper: modeling, analysis, and algorithm. First, a comprehensive LCD motion blur model is presented, in which human-eye-tracking limits are taken into consideration. Second, a complete analysis of spatiotemporal equivalence is provided and verified using real video sequences. Third, an LCD motion blur reduction algorithm is proposed. The proposed algorithm solves an l 1 -norm regularized least-squares minimization problem using a subgradient projection method. Numerical results show that the proposed algorithm gives higher peak SNR, lower temporal error, and lower spatial error than motion-compensated inverse filtering and Lucy-Richardson deconvolution algorithm, which are two state-of-the-art LCD deblurring algorithms.
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ISSN:1057-7149
1941-0042
1941-0042
DOI:10.1109/TIP.2011.2109728