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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.

Papers
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Image information and visual quality

TL;DR: An image information measure is proposed that quantifies the information that is present in the reference image and how much of this reference information can be extracted from the distorted image and combined these two quantities form a visual information fidelity measure for image QA.
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Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures

TL;DR: This article has reviewed the reasons why people want to love or leave the venerable (but perhaps hoary) MSE and reviewed emerging alternative signal fidelity measures and discussed their potential application to a wide variety of problems.
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A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms

TL;DR: This paper presents results of an extensive subjective quality assessment study in which a total of 779 distorted images were evaluated by about two dozen human subjects and is the largest subjective image quality study in the literature in terms of number of images, distortion types, and number of human judgments per image.
Book

Handbook of Image and Video Processing

Alan C. Bovik
TL;DR: The Handbook of Image and Video Processing contains a comprehensive and highly accessible presentation of all essential mathematics, techniques, and algorithms for every type of image and video processing used by scientists and engineers.
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Multichannel texture analysis using localized spatial filters

TL;DR: An interpretation of image texture as a region code, or carrier of region information, is emphasized and examples are given of both types of texture processing using a variety of real and synthetic textures.