High Resolution Optical and SAR Satellite Image Processing for Disaster Management using Hierarchical MRFs

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• Prof. Josiane Zerubia, IEEE Distinguished Lecturer, INRIA, France
• Friday 02 December 2016, 15:00-16:00
• LR4, Cambridge University Engineering Department.

If you have a question about this talk, please contact Prof. Ramji Venkataramanan.

In this talk, we describe a novel classification approach for multi-resolution, multi-sensor (optical and synthetic aperture radar (SAR)) and/or multi-band images. This challenging image processing problem is of great importance for various remote sensing monitoring applications and has been scarcely addressed so far. To deal with this classification problem, we propose a two-step explicit statistical model. We first design a model for the multi-variate joint class-conditional statistics of the co-registered input images at each resolution. We then plug the estimated joint probability density functions into a hierarchical Markovian model based on a quad-tree structure, where each tree-scale corresponds to the different input image resolutions and to the corresponding multi-scale decimated wavelet transforms, thus preventing a strong re-sampling of the initial images. To obtain the classification map, we resort to an estimator of the marginal posterior mode. We integrate a prior update in this model in order to improve the robustness of the proposed classifier against noise and speckle. The resulting classification performance is illustrated on several remote sensing multi-resolution datasets including very high resolution and multi-sensor images acquired by COSMO -SkyMed and GeoEye-1 satellites.

This talk is supported by the IEEE through the IEEE Distinguished Lecturer program.

BIO: Josiane Zerubia has been a permanent research scientist at INRIA since 1989 and director of research since July 1995. She was head of the PASTIS remote sensing laboratory (INRIA Sophia-Antipolis) from mid-1995 to 1997 and of the Ariana research group (INRIA/CNRS/University of Nice), which worked on inverse problems in remote sensing and biological imaging, from 1998 to 2011. Since January 2012, she has been head of Ayin research group (INRIA-SAM) dedicated to models of spatio-temporal structure for high resolution image processing with a focus on remote sensing and skincare imaging. She has been professor at SUPAERO (ISAE) in Toulouse since 1999. Before that, she was with the Signal and Image Processing Institute of the University of Southern California (USC) in Los-Angeles as a postdoc. She also worked as a researcher for the LASSY (University of Nice/CNRS) from 1984 to 1988 and in the Research Laboratory of Hewlett Packard in France and in Palo-Alto (CA) from 1982 to 1984. She received the MSc degree from the Department of Electrical Engineering at ENSIEG , Grenoble, France in 1981, the Doctor of Engineering degree, her PhD and her ‘Habilitation’, in 1986, 1988, and 1994 respectively, all from the University of Nice Sophia-Antipolis, France.

She is a Fellow of the IEEE (2003- ) and IEEE SP Society Distinguished Lecturer (2016-2017). She was a member of the IEEE IMDSP TC (SP Society) from 1997 till 2003, of the IEEE BISP TC (SP Society) from 2004 till 2012 and of the IVMSP TC (SP Society) from 2008 till 2013. She was associate editor of IEEE Trans. on IP from 1998 to 2002, area editor of IEEE Trans. on IP from 2003 to 2006, guest co-editor of a special issue of IEEE Trans. on PAMI in 2003, member of the editorial board of IJCV from 2004 till March 2013 and member-at-large of the Board of Governors of the IEEE SP Society from 2002 to 2004. She has also been a member of the editorial board of the French Society for Photogrammetry and Remote Sensing (SFPT) since 1998, of the Foundation and Trends in Signal Processing since 2007 and member-at-large of the Board of Governors of the SFPT since September 2014. She has been associate editor of the on-line resource « Earthzine » (IEEE CEO and GEOSS ) since 2006.

Her main research interest is in image processing using probabilistic models. She also works on parameter estimation, statistical learning and optimization techniques.

This talk is part of the Signal Processing and Communications Lab Seminars series.

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