Multispectral Image Fusion

#Multispectral #image #fusion #distinguished #lecture #Erik #Brasch
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Current trends in artificial intelligence/machine learning (AI/ML) have increased the interest in multi-source techniques, especially those of multispectral image fusion. The presentation will highlight developments in image fusion applications, methods, and evaluation.

Image fusion applications include: surveillance, medical, and inspection utilizing multi-focus, multi-resolution, multi-view, multi-exposure, multi-spectrum, and multi-modal data.  Image fusion methods include statistical processing, wavelet transforms as well as recent methods with generative adversarial networks (GANs). Evaluation includes data sets and collection, performance metrics, and quantitative and qualitative performance. 

The talk will focus on basic methods and approaches, provide examples, and discuss guidelines as well as recent trends in image fusion. Examples and references will be provided so as to point the audience to more details on fundamental constructs towards their areas of interest. 



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  • Date: 10 Sep 2020
  • Time: 04:30 PM to 05:30 PM
  • All times are (GMT-05:00) US/Eastern
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  • Co-sponsored by CH02182 - Washington/Baltimore/No VA Jt Sections Chap,CAS04
  • Starts 24 August 2020 12:00 AM
  • Ends 09 September 2020 11:59 PM
  • All times are (GMT-05:00) US/Eastern
  • No Admission Charge


  Speakers

Erik Blasch, PhD, MBA of Air Force Office of Scientific Research

Topic:

Multispectral Image Fusion

Current trends in artificial intelligence/machine learning (AI/ML) have increased the interest in multi-source techniques, especially those of multispectral image fusion. The presentation will highlight developments in image fusion applications, methods, and evaluation.

Image fusion applications include: surveillance, medical, and inspection utilizing multi-focus, multi-resolution, multi-view, multi-exposure, multi-spectrum, and multi-modal data.  Image fusion methods include statistical processing, wavelet transforms as well as recent methods with generative adversarial networks (GANs). Evaluation includes data sets and collection, performance metrics, and quantitative and qualitative performance. 

The talk will focus on basic methods and approaches, provide examples, and discuss guidelines as well as recent trends in image fusion. Examples and references will be provided so as to point the audience to more details on fundamental constructs towards their areas of interest. 

Biography:

 

ERIK BLASCH is a program officer at the United States Air Force Research Laboratory (AFRL) – Air Force Office of Scientific Research (AFOSR). Previously, he was a Principal Scientist at AFRL in Rome, NY (2012-16); Exchange Scientist to Defence Research and Development Canada (DRDC) at Valcartier, Quebec (2010-12); and Information Fusion Evaluation Tech Lead at AFRL in Dayton, OH (2000-09). Dr. Blasch has been an Adjunct Associate Engineering Processor at Wright State University teaching signal processing, target tracking, and information fusion.

Dr. Blasch was a founder member of the International Society of Information Fusion (ISIF) (ww.isif.org), 2007 President, and Board of Governors (BoG) member (2000-10). He served on the IEEE Aerospace and Electronics Systems Society (AESS) BoG (2011-16), distinguished lecturer (2012-20), and co-chair of 7 conferences. He has focused on information fusion, target tracking, pattern recognition, and robotics research compiling 850 scientific papers, 32 patents, and 33 team-robotics wins. His coauthored books include High-Level Information Fusion Management and Systems Design, (Artech House, 2012), Advances and Applications of DSmT for Information Fusion (American Research Press, 2015), Context-Enhanced information Fusion (Springer, 2016), Multispectral Image Fusion and Colorization (SPIE, 2018), Handbook of Dynamic Data Driven Applications Systems (Springer, 2018), and Deep Learning for Radar and Communications Automatic Target Recognition (Artech, 2020).

Dr. Blasch received his B.S. in Mechanical Engineering from the Massachusetts Institute of Technology in 1992 and M.S. degrees in Mechanical (’94), Health Science(’95), and Industrial Engineering (human factors)(’95) from Georgia Tech and attended the Univ. of Wisconsin for a MD/PhD in Neuroscience/ME until being called to military service in 1996 to the United States Air Force. He completed an MBA(’98), MSEE(’98), MSEcon(’99), and PhD(’99) in Electrical Engineering from Wright State University and is a graduate of Air War College(’08). He is the recipient of the Military Sensing Symposium (MSS) Mignogna Leadership in Data Fusion Award, IEEE AESS Mimno Best Paper Award, and IEEE Russ Bio-Engineering Award. He is an Associate Fellow of American Institute of Aeronautics and Astronautics (AIAA), Fellow of the Society of Photo-Optical and Instrumentation Engineers (SPIE), and Fellow of Institute of Electrical and Electronics Engineers (IEEE).