Wavelets on Graphs: Theory and Applications

March 22, 2011
Time: 11:00am-12:00pm
Interschool Lab, 7th floor CEPSR
Hosted by: Prof. Shih-Fu Chang
Speaker: Prof. Antonio Ortega, University of Southern California

Abstract

Wavelet transforms have become popular tools for numerous signal processing tasks, from compression to analysis or denoising. These transforms provide a class of signal representations with flexible time (or space) and frequency localization. Recent extensions of these transforms have been targeted to incorporate arbitrary directionality in the transform (e.g., Bandelets, Contourlets).

In this presentation we focus on wavelet-like, multiresolution transforms for datasets that are defined on arbitrary graphs. This is an area that has started to attract some interest only very recently and yet has the potential to have significant impact in a number of applications. Examples of datasets that could be seen as graphs include data distributed in a sensor network, image data traversed in arbitrary fashion, or data available in online social networks.

We first provide an overview of our recent work in the development of wavelets for graphs data. In particular we show constructions based on lifting as well as an example design based simple graph filters. These are among the first critically sampled wavelet representations that have been proposed for arbitrary graph data.

We then provide an overview of two potential applications of these transforms in i) distributed data gathering in a sensor network and ii) image compression.

Speaker Biography

Antonio Ortega received the Telecommunications Engineering degree from the Universidad Politecnica de Madrid, Madrid, Spain in 1989 and the Ph.D. in Electrical Engineering from Columbia University, New York, NY in 1994. At Columbia he was supported by a Fulbright scholarship.

In 1994 he joined the Electrical Engineering department at the University of Southern California (USC), where he is currently a Professor and Associate Chair of EE-Systems. He has served as director of the Signal and Image Processing Institute at USC. He is a Fellow of the IEEE, and a member of ACM. He has been Chair of the Image and Multidimensional Signal Processing (IMDSP) technical committee and a member of the Board of Governors of the IEEE Signal Processing Society. He has been technical program co-chair of ICIP 2008, MMSP 1998 and ICME 2002. He is currently Associate Editor (AE) for the IEEE Transactions on Image Processing and Area Editor (Feature Articles) of the IEEE Signal Processing Magazine. In addition to a previous stint as AE for T-IP he has also served as AE for the IEEE Signal Processing Letters and for the EURASIP Journal on Advances in Signal Processing. He received the NSF CAREER award, the 1997 IEEE Communications Society Leonard G. Abraham Prize Paper Award, the IEEE Signal Processing Society 1999 Magazine Award and the 2006 EURASIP Journal of Advances in Signal Processing Best Paper Award.

His research interests are in the areas of multimedia compression, communications and signal analysis. His recent work is focusing on distributed compression, multiview coding, error tolerant compression, wavelet-based signal analysis and information representation in wireless sensor networks. His work at USC has been or is being funded by agencies such as NSF, NASA, DOE, as well as a number of companies. Over 25 PhD students have completed their PhD thesis work under his supervision at USC and his work has led to over 250 publications in international conferences and journals.


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