Event date:
Oct 22 2021 11:30 am

Artificial Intelligence on the Sphere: Spatial Slepian Transform for Localized Variation Analysis

Dr. Zubair Khalid
Processing and extraction of information from the data defined on the sphere find applications in cosmology, geophysics, planetary sciences, 3D antenna radiation design, medical imaging, computer vision, virtual reality, wireless communication, acoustics and computer graphics, to name a few. To support spatially localized data analysis in these applications, we present spatial-Slepian transform (SST). We employ well-optimally concentrated Slepian functions, which are obtained as a solution of the Slepian spatial-spectral concentration problem of finding bandlimited and spatially optimally concentrated functions on the sphere, to formulate the proposed transform. Due to the optimal energy concentration of Slepian functions in the spatial domain, the proposed spatial-Slepian transform allows us to probe spatially localized content of the signal. Furthermore, we present an inverse transform to recover the signal from its spatial-Slepian coefficients, formulate an algorithm for fast computation of SST, and carry out computational complexity analysis. We compute the spatial variance of spatial-Slepian coefficients and conduct experiments to show that spatial-Slepian coefficients have better spatial localization than scale-discretized wavelet coefficients. We present the formulation of SST for zonal Slepian functions, which are spatially optimally concentrated in the axisymmetric polar cap region and provide an illustration using a bandlimited Earth topography map.

To demonstrate the utility of the proposed transform, we carry out localized variation analysis, in which we employ SST to detect hidden localized variations in the signal. We illustrate, through a toy example, that spatial-Slepian transform yields a much better estimate of the underlying region of hidden localized variations than scale-discretized wavelet transform.

Dr. Zubair Khalid will be talking about “Artificial Intelligence on the Sphere: Spatial Slepian Transform for Localized Variation Analysis” on 22 October 2021 at 11:30 am.  

This seminar is being organized by the Department of Electrical Engineering as Fall 2022 Research Seminar Series. The next seminar will be on 19 November 2021, Friday. 

Please join via Zoom meeting link:  

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About the Speaker:

Dr. Zubair Khalid (Senior Member, IEEE) received BSc (First-class Hons.) degree in Electrical Engineering from the University of Engineering and Technology, Lahore, Pakistan in 2008, and the PhD degree in engineering from The Australian National University of Canberra, ACT, Australia in August 2013. He is currently working as Assistant Professor with the Department of Electrical Engineering at SBASSE, LUMS. His research interests include signal processing and wireless communication, including the development of novel signal processing techniques for signals on the sphere and the application of stochastic geometry in wireless ad-hoc networks. He was awarded University Gold Medal and Industry Gold Medals from Siemens and Nespak for his overall outstanding performance in electrical engineering during his undergraduate studies. He was the recipient of the Endeavour International Postgraduate Award for PhD studies. Since 2020, he has been a Member of the Editorial Board (Associate Editor) for the IEEE Signal Processing Letters.