Prof. Al Bovik of Texas ECE has been named the 2019 recipient of the IEEE Fourier Award for Signal Processing. The IEEE Fourier Award for Signal Processing was established in 2012 and is awarded to an individual or team based on "impact on the field of signal processing technology, including innovation; leadership; honors or seminal contributions as evidenced by publications or patents or transition to practice; and quality of nomination." Prof. Bovik was selected "for seminal contributions and high-impact innovations to the theory and application of perception-based image and video processing."
Prof. Bovik holds the Cockrell Family Endowed Regents Chair in Engineering at The University of Texas at Austin, where he is Director of the Laboratory for Image and Video Engineering (LIVE). Dr. Bovik received Television’s highest honor, an individual Primetime Emmy Award for Outstanding Achievement in Engineering Development from the Academy of Television Arts and Sciences (The Television Academy) in October 2015, for his work on the development of video quality prediction models which have become standard tools in broadcast and post-production houses throughout the television industry. He has published over 800 technical articles in these areas and holds several U.S. patents. His publications have been cited more than 75,000 times in the literature, his current H-index is over 100, and he is listed as a Highly-Cited Researcher by Thompson Reuters. His several books include the companion volumes The Essential Guides to Image and Video Processing (Academic Press, 2009).
IEEE had this to say about Prof. Bovik:
"For nearly four decades, Al Bovik has made extraordinary contributions to the field of Image Signal Processing that are most deserving of the IEEE Fourier Award. He has received every major IEEE SPS award, six IEEE SPS and IEEE CAS journal paper awards, and important non-IEEE awards. His impact is sky-high: he has been cited >70,000 times, with an H-index >100."
"It is hard to overstate Al’s contributions to image signal processing, ranging from his early, influential work in nonlinear filtering, foveated image processing, and perception-based texture processing, to later high-profile work on picture quality prediction. His research has been exemplified by pioneering cross-disciplinary research linking traditional image signal processing with statistical theory and modern visual neuroscience to solve important, high-impact practical problems."