Title: Hyperspectral Imaging in Environmental Informatics

Speaker: Zhou Jun

Date & Time: 19^th May, 10:00

Venue: C505

Abstract: Comparing to grayscale, RGB and multi-spectral images that capture data in one, three, or several wavelength bands, hyperspectral imagery contains tens or hundreds of continuous bands that provide rich information on the spectral and spatial distribution of materials of the objects in a scene. This has opened great opportunity for environment and computer vision research which is heavily relied on the capacity and quality of images for object detection and image classification. In this talk, I will give an overview on the latest development of the hyperspectral imaging technology, and show the advantages of performing spectral-spatial image analysis for better scene understanding. Particular focus will be put on sparsity constrained hyperspectral image classification and unmixing, with their applications to land cover, plant, and soil analysis.

Bio: Jun Zhou received the B.S. degree in Computer Science from Nanjing University of Science and Technology, China, in 1996, the M.S. degree in Computer Science from Concordia University, Canada, and the Ph.D. degree in computing science from the University of Alberta, Canada, in 2006. He joined the School of Information and Communication Technology in Griffith University in June 2012. At the same time, he is an adjunct visiting fellow in the Research School of Computer Science at the Australian National University (ANU) and a visiting scientist in CSIRO. Prior to his appointment in Griffith University, he had been a research fellow in ANU, and a researcher at NICTA Canberra Lab. Dr Zhou was a winner of the Discovery Early Career Research Awardfrom the Australian Research Council in 2012. His research interests are in pattern recognition, computer vision, hyperspectral imaging, and their applications to environmental informatics.