Image Restoration (eBook, PDF)

Fundamentals and Advances
Redaktion: Gunturk, Bahadir Kursat; Li, Xin

• Format: PDF

Produktbeschreibung

Addressing a variety of applications, this book covers a wide range of topics pertaining to image restoration. Topics covered include image denoising, document image analysis, remote sensing applications, and image formation modeling. Content also addresses blind image restoration, iterative optimization techniques, learning-based image restoration, and non-local approach, as well as super-resolution, multi-spectral restoration, and video inpainting. Contributors from various countries help readers understand the essentials, the state of the art, and the research directions. The text features background material, mathematical content, a survey of the methods, examples, comparisons, and a bibliography.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 378
• Erscheinungstermin: 3. September 2018
• Englisch
• ISBN-13: 9781439869567
• Artikelnr.: 40067036

Autorenporträt

Bahadir K. Gunturk received his B.S. degree from Bilkent University, Turkey, and his Ph.D. degree from the Georgia Institute of Technology in 1999 and 2003, respectively, both in electrical engineering. Since 2003, he has been with the Department of Electrical and Computer Engineering at Louisiana State University, where he is an associate professor. His research interests are in image processing and computer vision. Dr. Gunturk was a visiting scholar at the Air Force Research Lab in Dayton, Ohio, and at Columbia University in New York City. He is the recipient of the Outstanding Research Award at the Center of Signal and Image Processing at Georgia Tech in 2001, the Air Force Summer Faculty Fellowship Program (SFFP) Award in 2011 and 2012, and named as a Flagship Faculty at Louisiana State University in 2009. Xin Li received his B.S. degree with highest honors in electronic engineering and information science from the University of Science and Technology of China, Hefei, in 1996, and his Ph.D. degree in electrical engineering from Princeton University, Princeton, New Jersey, in 2000. He was a member of the technical staff with Sharp Laboratories of America, Camas, Washington, from August 2000 to December 2002. Since January 2003, he has been a faculty member in the Lane Department of Computer Science and Electrical Engineering at West Virginia University. He is currently a tenured associate professor at that school. His research interests include image/video coding and processing. Dr. Li received a Best Student Paper Award at the Visual Communications and Image Processing Conference in 2001; a runner-up prize of Best Student Paper Award at the IEEE Asilomar Conference on Signals, Systems and Computers in 2006; and a Best Paper Award at the Visual Communications and Image Processing Conference in 2010.

Inhaltsangabe

Image Denoising: Past, Present, and Future. Fundamentals of Image
Restoration. Restoration in the Presence of Unknown Spatially Varying Blur.
Image Denoising and Restoration Based on Nonlocal Means.
Sparsity-Regularized Image Restoration: Locality and Convexity Revisited.
Resolution Enhancement Using Prior Information. Transform Domain-Based
Learning for Super Resolution Restoration. Super Resolution for
Multispectral Image Classification. Color Image Restoration Using Vector
Filtering Operators. Document Image Restoration and Analysis as Separation
of Mixtures of Patterns: From Linear to Nonlinear Models. Correction of
Spatially Varying Image and Video Motion Blur Using a Hybrid Camera.