Course name：Wavelets and Sparse Signal Processing
Textbooks and references
(1)Stéphane Mallat, A Wavelet Tour to Signal Processing, The Sparse Way, Third Edition, Elsevier, 2009
(2)Michael Elad, Sparse and Redundant Representations, From Theory to Applications in Signal and Image Processing, Springer, 2010
(3)Alan V. Oppenheim, Signals & Systems, Second Edition, Publishing House of Electronics Industry of China
This course aims at presenting the basic theory of wavelet transform-based multimedia signal processing to graduate students. Starting from the basic idea of time-frequency analysis, the course presents the basic definition and property of wavelet transform, filter bank and multi-scale geometry analysis, sparse representation, and other signal processing methods. The course also provides multimedia signal processing tools developed recently based on the idea of wavelet, such as wavelet scattering transform and graph wavelet. It also covers the application method and latest developments of signal processing approaches based on wavelet analysis, fractal and sparse representation in aspect of image and video signal processing.
|1||Fundamentals||Lecture01 02 03 04|
|2||Time Meets Frequency||Lecture05|
|6||Multiscale Geometry Analysis||Lecture09|
|7||Lifting Wavelet and Filterbank||Lecture10|
Requirements and grading
Homework and attendance: 20% Homework should be written in ENGLISH.
Projects: 40% Requirements
firstname.lastname@example.org (TA, Wen Fei)
email@example.com (TA, Tianran Wu)
Institute of Media, Information, and Network (MIN Lab)