Mathematics in Image Processing
About this Title
Hongkai Zhao, University of California, Irvine, Irvine, CA, Editor
Publication: IAS/Park City Mathematics Series
Publication Year: 2013; Volume 19
ISBNs: 978-0-8218-9841-3 (print); 978-0-8218-9870-3 (online)
MathSciNet review: MR3098079
MSC: Primary 94A12; Secondary 92C10, 92C55, 94A08
The theme of the 2010 PCMI Summer School was Mathematics in Image Processing in a broad sense, including mathematical theory, analysis, computation algorithms and applications. In image processing, information needs to be processed, extracted and analyzed from visual content, such as photographs or videos. These demands include standard tasks such as compression and denoising, as well as high-level understanding and analysis, such as recognition and classification. Centered on the theme of mathematics in image processing, the summer school covered quite a wide spectrum of topics in this field. The summer school is particularly timely and exciting due to the very recent advances and developments in the mathematical theory and computational methods for sparse representation.
This volume collects three self-contained lecture series. The topics are multi-resolution based wavelet frames and applications to image processing, sparse and redundant representation modeling of images and simulation of elasticity, biomechanics, and virtual surgery. Recent advances in image processing, compressed sensing and sparse representation are discussed.
Graduate students and research mathematicians interested in the mathematics of image processing.
Table of Contents
- MRA-based wavelet frames and applications
- Five lectures on sparse and redundant representations modelling of images
- Simulation of elasticity, biomechanics, and virtual surgery