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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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Journal ArticleDOI
Spatiotemporal Feature Integration and Model Fusion for Full Reference Video Quality Assessment
TL;DR: In rigorous experiments, the proposed algorithms demonstrate the state-of-the-art performance on multiple video applications and are made available as a part of the open source package in https://github.com/Netflix/vmaf.
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Maximum-likelihood techniques for joint segmentation-classification of multispectral chromosome images
TL;DR: It is shown that the proposed multispectral joint segmentation-classification method outperforms past grayscale segmentation methods when decomposing touching chromosomes and can also be used as a reliable indicator of errors in segmentation, errors in classification, and chromosome anomalies.
Journal ArticleDOI
A Subjective and Objective Study of Stalling Events in Mobile Streaming Videos
TL;DR: A new mobile video quality database that contains videos afflicted with distortions caused by 26 different stalling patterns, and is making the database publicly available in order to help the advance state-of-the-art research on user-centric mobile network planning and management.
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Oriented Correlation Models of Distorted Natural Images With Application to Natural Stereopair Quality Evaluation
TL;DR: A new no-reference stereoscopic/3D IQA framework is developed, dubbed stereoscopic-3D blind image naturalness quality index, which utilizes both univariate and generalized bivariate natural scene statistics (NSS) models.
Proceedings ArticleDOI
Unifying analysis of full reference image quality assessment
TL;DR: The SSIM model is shown to be equivalent to models of contrast gain control of the HVS and the Information Fidelity Criterion is a monotonic function of the structure term of the SSIM index applied in the sub-band filtered domain.