Wavelets on Graphs: Theory and Applications
|Organization || Signal and Image Processing Institute Department of Electrical Engineering University of Southern California|
|Location||Engineering Building II Room 1230|
|Date||November 16, 2012 12:50 PM|
USAWavelet 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.
Along the way we provide an overview of two potential applications of these transforms in i) distributed data gathering in a sensor network and ii) image/video compression.
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 has served as Associate Editor of the IEEE Transactions on Image Processing, Signal Processing Letters and Area Editor (Feature Articles) of the IEEE Signal Processing Magazine. He is the inaugural Editor-in-Chief of the APSIPA Transactions on Signal and Information 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, 2006 EURASIP Journal of Advances in Signal Processing Best Paper Award and the ICIP 2011 best paper award.
His research interests are in the areas of multimedia compression, communications and signal analysis.