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Alan C. Bovik
Researcher at University of Texas at Austin
Publications - 872
Citations - 120104
Alan C. Bovik is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Image quality & Video quality. The author has an hindex of 102, co-authored 837 publications receiving 96088 citations. Previous affiliations of Alan C. Bovik include University of Illinois at Urbana–Champaign & University of Sydney.
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Subjective and Objective Quality Assessment of High Frame Rate Videos
TL;DR: A new subjective resource, called the LIVE-YouTube-H FR (LIVE-YT-HFR) dataset, which is comprised of 480 videos having 6 different frame rates, obtained from 16 diverse contents, and is made available online for public use and evaluation purposes.
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No-training, no-reference image quality index using perceptual features
TL;DR: A universal no-reference image quality assessment (QA) index that does not require training on human opinion scores is proposed that accords closely with human subjective judgments of diverse distorted images.
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Using chromatic information in edge-based stereo correspondence
John R. Jordan,Alan C. Bovik +1 more
TL;DR: The results demonstrate that the use of chromatic information can significantly reduce the ambiguity between potential matches, resulting in increased algorithm accuracy as well as increased algorithm speed.
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The SIVA Demonstration Gallery for signal, image, and video processing education
TL;DR: This paper describes tools and techniques that facilitate a gentle introduction to fascinating concepts in signal and image processing and provides a library of more than 50 visualization modules that accentuate the intuitive aspects of DSP algorithms as a free didactic tool to the broad signal andimage-processing community.
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Using chromatic information in dense stereo correspondence
John R. Jordan,Alan C. Bovik +1 more
TL;DR: The chromatic photometric constraint, which is used to specify a mathematical optimality criterion for solving the dense stereo correspondence problem, is developed, and is a theoretical construction for developing dense stereo correspondence algorithms which use chromatic information.