bilitation degree from the University Paris XI, Paris, France. He is Senior Scientist at the ... from 1999 to 2000. He has been an Associate Professor of signal and image pro- ... the Computer Science Department, Technion. On May 2007, he was ...
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Introduction to the issue on Adaptive Sparse Representation of Data and Applications in Signal and Image Processing
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HE complex structure of natural signals and images requires adaptive tools in order to make use of their intricate redundancies. To capture this complexity, we have witnessed a flurry of research activities where researchers spanning a diverse range of viewpoints have advocated the use of sparsity and overcomplete signal/image representations. It has turned out that exploiting sparsity and overcompleteness offers striking benefits in a wide range of signal/image processing applications. These generic methods however have limitations in terms of computational efficiency or theoretical ability to extract specific patterns. Indeed, complex signals such as turbulent textures, geometrical astronomical data, or audio signals can be unsatisfactorily represented in current fixed redundant dictionaries. Thus, choosing an appropriate dictionary is a key step towards an efficient sparse representation. A core idea here is the adaptivity of the transforms to the morphological content of data. This special issue gathers a broad range of methods, algorithms, theoretical results, and applications in the area of adaptive sparse approximation. The special issue opens with a nice and comprehensive review by Gabriel Peyré on state-of-the-art approaches for adaptive signal and image representation. It is then followed by original works in different fields that cover the following topics: 1) six papers are dedicated to structured and adaptive sparse representations and recovery; 2) the three following papers are on dictionary learning, where the dictionary may be partially structured or not;
3) finally, the special issue includes several application papers including audio signal processing, image processing, hyperspectral and astronomical imaging. This special issue makes an important step in this very active and exciting field of high-dimensional data processing. We deeply believe that the quest for understanding and handling efficiently such data sources is far from being exhausted and we expect the coming years to witness novel insights and breakthroughs in this field.
Digital Object Identifier 10.1109/JSTSP.2011.2162154
JEAN-LUC STARCK, Lead Guest Editor Service d’Astrophysique, CEA/Saclay 91191 Gif-sur-Yvette, France JALAL FADILI, Guest Editor GREYC CNRS-Université de Caen 14050 Caen Cedex, France MICHAEL ELAD, Guest Editor The Technion–Israel Institute of Technology Haifa 32000, Israel ROBERT NOWAK, Guest Editor University of Wisconsin-Madison Madison, WI 53706 USA PANAGIOTIS TSAKALIDES, Guest Editor University of Crete and FORTH-ICS GR-700 13 Heraklion, Crete, Greece
Jean-Luc Starck received the Ph.D. degree from the Nice Observatory, Nice, France, and the Habilitation degree from the University Paris XI, Paris, France. He is Senior Scientist at the Institute of Research into the Fundamental Laws of the Universe, CEA-Saclay, Gif-sur-Yvette, France. He was a visitor at the European Southern Observatory (ESO) in 1993, at UCLA in 2004, and at Stanford’s Statistics Department in 2000 and 2005. He has been a Researcher since 1994 at CEA-Saclay, Institute of Research into the Fundamental Laws of the Universe. His research interests include image processing, statistical methods in astrophysics, and cosmology. He is an expert in multiscale methods such wavelets and curvelets. He is leader of the CosmoStat Laboratory at CEA and he is involved in the PLANCK and EUCLID ESA project. He has published more than 100 papers in different areas in scientific journals and he is also author of three books entitled Image Processing and Data Analysis: The Multiscale Approach (Cambridge Univ. Press, 1998), Astronomical Image and Data Analysis (Springer, 2006), and Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity (Cambridge Univ. Press, 2010). 1932-4553/$26.00 © 2011 IEEE
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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, VOL. 5, NO. 5, SEPTEMBER 2011
Jalal Fadili graduated from the Ecole Nationale Supérieure d’Ingénieurs (ENSI) de Caen, Caen, France, and received the M.Sc., Ph.D., and Habilitation degrees in signal and image processing from the University of Caen. He was a Research Associate with the University of Cambridge (MacDonnel-Pew Fellow), Cambridge, U.K., from 1999 to 2000. He has been an Associate Professor of signal and image processing since September 2001 at ENSI. He was a visitor at several universities (QUT-Australia, Stanford University, CalTech, EPFL). He is the coauthor of a book entitled Sparse Signal and Image Processing: Wavelets, Curvelets, Morphological Diversity (Cambridge Univ. Press, 2010). His research interests include statistical approaches in signal and image processing, inverse problems, computational harmonic analysis, optimization, and sparse representations. His areas of application include medical and astronomical imaging.
Michael Elad (M’98–SM’08) received the B.Sc., M.Sc., and D.Sc. degrees from the Department of Electrical Engineering, The Technion–Israel Institute of Technology, in 1986, 1988, and 1997, respectively. From 1988 to 1993, he served in the Israeli Air Force. From 1997 to 2000, he worked at Hewlett-Packard Laboratories Israel as an R&D Engineer. From 2000 to 2001, he headed the research division at Jigami Corporation, Israel. During the years 2001 to 2003, He held a research-associate position at Stanford University. Since late 2003, he has been a faculty member at the Computer Science Department, Technion. On May 2007, he was tenured to an associate professorship, and on July 2010 he was promoted to full professorship. He works in the field of signal and image processing, specializing in particular on inverse problems, sparse representations, and super resolution. Prof. Elad received the Technion’s Best Lecturer Award six times, he is the recipient of the Solomon Simon Mani Award for excellence in teaching in 2007, and he is also the recipient of the Henri Taub Prize for academic excellence (2008) and the Hershel–Rich prize (2010) for innovation. He is currently serving as an Associate Editor for SIAM Journal on Imaging Sciences (SIIMS).
Robert Nowak (M’95–SM’04–F’10) received the B.S., M.S., and Ph.D. degrees in electrical engineering from the University of Wisconsin-Madison in 1990, 1992, and 1995, respectively. He was a Postdoctoral Fellow at Rice University in 1995-1996, an Assistant Professor at Michigan State University from 1996 to 1999, held Assistant and Associate Professor positions at Rice University from 1999 to 2003, and is now the McFarland–Bascom Professor of Engineering at the University of Wisconsin-Madison. He has held visiting positions at INRIA, Sophia-Antipolis (2001), and Trinity College, Cambridge (2010). Prof. Nowak has served as an Associate Editor for the IEEE TRANSACTIONS ON IMAGE PROCESSING and the ACM Transactions on Sensor Networks, and as the Secretary of the SIAM Activity Group on Imaging Science. He was General Chair for the 2007 IEEE Statistical Signal Processing Workshop and Technical Program Chair for the 2003 IEEE Statistical Signal Processing Workshop and the 2004 IEEE/ACM International Symposium on Information Processing in Sensor Networks. He received the General Electric Genius of Invention Award (1993), the National Science Foundation CAREER Award (1997), the Army Research Office Young Investigator Program Award (1999), the Office of Naval Research Young Investigator Program Award (2000), and IEEE Signal Processing Society Young Author Best Paper Award (2000). His research interests include signal processing, machine learning, imaging and network science, and applications in communications, bioimaging, and systems biology.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, VOL. 5, NO. 5, SEPTEMBER 2011
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Panagiotis Tsakalide (M’95) received the Diploma degree in electrical engineering from the Aristotle University of Thessaloniki, Thessaloniki, Greece, in 1990, and the Ph.D. degree in electrical engineering from the University of Southern California (USC), Los Angeles, in 1995. He is a Professor of Computer Science at the University of Crete, and a Researcher with the Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH-ICS), Heraklion, Crete, Greece. From 2004 to 2006, he served as the Department Chairman. From 1999 to 2002, he was with the Department of Electrical Engineering, University of Patras, Patras, Greece. From 1996 to 1998, he was a Research Assistant Professor with the Signal and Image Processing Institute, USC, and he consulted for the U.S. Navy and Air Force. His research interests lie in the field of statistical signal processing with emphasis in non-Gaussian estimation and detection theory, and applications in sensor networks, audio, imaging, and multimedia systems. He has coauthored over 100 technical publications in these areas, including 25 journal papers. He is the PI of the 1.3 M euros FP7 MC-IAPP "CS-ORION" project (2010-2014) conducting research on compressed sensing for remote imaging in aerial and terrestrial surveillance. He is a member of the ERCIM Network of Innovation/Technology and Knowledge Transfer Experts (I-Board).
