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Motion‐blur evaluation: A comparison of approaches
Author(s) -
Becker Michael E.
Publication year - 2008
Publication title -
journal of the society for information display
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 52
eISSN - 1938-3657
pISSN - 1071-0922
DOI - 10.1889/jsid16.10.989
Subject(s) - computer science , computer vision , motion blur , artificial intelligence , convolution (computer science) , observer (physics) , repeatability , pixel , mathematics , image (mathematics) , physics , statistics , quantum mechanics , artificial neural network
Abstract— In this paper, the results obtained from two independent evaluations of motion‐blur effects with respect to the agreement between the two different approaches used, imaging and non‐imaging, are analyzed. The measurements have been carried out in different laboratories by different operators without the prior intention of a subsequent analysis as presented here. The resulting data is analyzed to quantify the repeatability of each instrument and, in a second step, the comparability of results from the two approaches is investigated. The imaging approach used in these experiments is based on a stationary high‐speed camera with temporal oversampling and numerical image‐data processing to obtain the intensity distribution on the retina of an observer under the condition of smooth pursuit eye tracking. Results from that approach are compared to results obtained from the evaluation of step responses acquired with optical transient recorders by frame‐period convolution. Measurements are carried out with a first LCD monitor with test patterns of both contrast polarities, with three velocities of translation, and four levels of gray. A second object of measurement is used for investigation of the effect of operator intervention in the process of evaluation of the imaging approach, especially on the determination of the reference levels that are needed for evaluation of the normalized blurred edge (NBE). Possible sources of uncertainties are identified for all approaches and instruments. Based on the analysis of that data, the practicability of step‐response‐based evaluations of the “blurred edge width/time” compared to the results obtained using the high‐speed imaging approach, as long as there is no motion‐dependent image processing, are confirmed.