http://www.poly.edu/node/8817 Title: A panorama on multiscale geometric representations, intertwining spatial, directional and frequency selectivity Speaker: Laurent Duval, IFP Energies nouvelles, France The quest for "optimal" representations in image processing and computer vision remains an very active area. The standard tasks of compression, denoising, restoration, require decompositions that trade off between efficiency and complexity, while achieving accurate rendering of smooth regions as well as reproducing faithful contours and textures. The inherent notion of scale in images has been satisfactorily captured by the large family of wavelets and pyramidal structures. Its most recent heirs (e.g. contourlets, curvelets, shearlets, dual-tree complex wavelets, etc.), born in the past 15 years, share a hybrid heritage highlighting the multiscale and oriented nature of edges and patterns in images. Such transforms typically exhibit redundancy, to improve sparsity in the transformed domain, and sometimes invariance with respect to simple geometric deformations (translation, rotation). This talk presents a panorama of these recent works on decompositions in multiscale, multi-orientation bases or dictionaries. [Joint work with Laurent Jacques, Caroline Chaux, Gabriel Peyré] Additional information: http://www.sciencedirect.com/science/article/pii/S0165168411001356 About the Speaker: Laurent Duval is a research amateur at IFP Energies nouvelles and occasionally teaches signal and image processing. He received a State Engineering degree in electrical engineering from École supérieure d'électricité (Supélec), a master's degree in pure and applied mathematics from Paul Verlaine University (Metz, France), and the PhD degree in signal processing from the University of Paris-Sud on the topic of seismic data compression. In 1998, he worked as a Research Assistant in the Multi-Dimensional Signal Processing Laboratory (MDSP Lab) at Boston University, Boston, MA. Since 2000, he conducts research in signal processing and image analysis with applications to geophysics, material characterization, analytical chemistry, and engine diagnosis. His research interests are in the area of non-stationnary digital signal and image processing, with a special emphasis on geometric wavelets, filter banks and time-frequency techniques, and their applications to denoising, filtering, detection, and data compression.