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15.2: Distinguished Paper : Assessment of Temporal Blur‐Reduction Methods Using a Computational Observer that Predicts Human Performance
Author(s) -
Liang Hongye,
Park Subok,
Gallas Brandon D.,
Badano Aldo,
Myers Kyle J.
Publication year - 2007
Publication title -
sid symposium digest of technical papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 44
eISSN - 2168-0159
pISSN - 0097-966X
DOI - 10.1889/1.2785466
Subject(s) - observer (physics) , reduction (mathematics) , computer science , contrast (vision) , artificial intelligence , computer vision , mathematics , physics , geometry , quantum mechanics
We report on a method to assess the impact of temporal blur reduction techniques based on measured or modeled device temporal characteristics with a contrast‐sensitive computational observer that predicts human performance. We applied the method to the comparison of different devices and temporal blur reduction approaches.