SPS Webinar, 29 October 2021: Empirical Wavelets

You are here

Inside Signal Processing Newsletter Home Page

Top Reasons to Join SPS Today!

1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.

10 years of news and resources for members of the IEEE Signal Processing Society

SPS Webinar, 29 October 2021: Empirical Wavelets

Upcoming SPS Webinar

Title: Empirical Wavelets
Date: 29 October 2021
Time: 2:00 PM ET (New York time)
Duration: Approximately 1 Hour
Presenters: Dr. Jérôme Gilles

Based on the IEEE Xplore® article: Empirical Wavelet Transform
Published: IEEE Transactions on Signal Processing, May 2013
Download: Original article will be made freely available for download for 48 hours from the day of the webinar, on IEEE Xplore®

 

Register for the Webinar

 

About the topic:

Adaptive (i.e., data-driven) methods have become very popular these last decades. Among the existing techniques, the empirical mode decomposition has proven to be very efficient in extracting accurate time-frequency information from non-stationary signals. However, it is a purely algorithmic method and lacks of solid theoretical foundations. To overcome this issue, we propose the construction of adaptive wavelets, called empirical wavelets. Their aim is to decompose a signal into its harmonic modes (i.e., amplitude modulated frequency modulated constituents). To reach this goal, we first detect the position of the wavelet supports in the Fourier domain by analyzing the signal spectrum, and then we build the corresponding wavelet filter bank. The transform is simply obtained by multiplication in the Fourier domain. We extend this idea to the 2D case for image processing by considering different types of classic Fourier partitions (tensor, Littlewood-Paley, curvelets, . . .). Finally, we propose a method, based on the Watershed transform, to create empirical wavelets on completely arbitrary supports. We explore some theoretical properties of the empirical wavelets in the continuous case and illustrate their efficiency in texture segmentation tasks.


About the presenter:

Jerome Gilles

Dr. Jérôme Gilles (J'74) received the M.S. degree in automatisms and signal processing from the Ecole Normale Supérieure of Cachan, France in 1999 and the Ph.D. degree in mathematics from the Ecole Normale Supérieure of Cachan, France in 2006 under the supervision of Prof. Yves Meyer (Gauss Prize 2010, Abel Prize 2017). He defended his “Habilitation à Diriger les Recherches " in 2012 under the mentorship of Prof. Jean-Michel Morel.

He held a scientist position from 2001 to 2010 in the French Ministry of Defense in the Department of Space, Observation, Intelligence and UAVs systems, as an expert in signal and image processing. From 2010 to 2014, he was an Assistant Adjunct Professor in the Department of Mathematics at the University of California, Los Angeles. He moved to the Department of Mathematics and Statistics at San Diego State University in 2014 as an assistant professor and was promoted to associate professor in 2018.

Dr. Gilles’ research interests include applied mathematics for signal/image modeling and analysis, textures analysis, signal/image restoration (neuroscience signal analysis, correction of atmospheric turbulence effects in long range imaging). He also devotes an important part of his time to study mathematical theories such as functional analysis, wavelets, partial differential equations and their applications for signal and image processing.

 

SPS on Twitter

  • The Brain Space Initiative Talk Series continues on Friday, 29 October when Dr. Selin Aviyente presents "Cross-Freq… https://t.co/Jxgu2soJCc
  • Join the Brain Space Initiative for another virtual mixing event on Wednesday, 27 October! Grab a coffee and meet w… https://t.co/KA3kuPUGw0
  • We're proud to sponsor a new journal, IEEE Transactions on Quantum Engineering, publishing regular, review, and tut… https://t.co/cZskrh9cvX
  • We are now seeking mentors and students for the launch of a new initiative, Mentoring Experiences for Underrepresen… https://t.co/i9SarNyKm9
  • This Wednesday, 13 October, join the Women in Signal Processing Committee for an IEEE Day webinar, "Promoting Diver… https://t.co/HrtVGqpwFx

SPS Videos


Signal Processing in Home Assistants

 


Multimedia Forensics


Careers in Signal Processing             

 


Under the Radar