Computational Imaging: Black Hole Shadows and Imaging Algorithms - Webinar

Join a captivating webinar in the Computational Imaging SPACE series featuring Katie Bouman from Caltech. Delve into the fascinating world of black hole imaging, exploring advanced techniques in computational imaging and signal processing. Learn about the groundbreaking work that led to the first-ever image of a black hole shadow. Discover the challenges of imaging at extreme distances and how innovative algorithms and optimal telescope designs are revolutionizing our understanding of the universe. Explore topics such as frequency space analysis, imaging algorithms, and methods to avoid shared human bias in scientific observations. Gain insights into critical velocity measurements, ring size determination, and the recovery of images from challenging datasets. Witness how simple experiments and simulations contribute to building confidence in black hole imaging results. Engage with applications of these techniques and participate in a technical question session to deepen your understanding of this cutting-edge field.

Introduction
Computational Imaging
Black Holes
Black Hole Shadow
Frequency Space
Measurements
Imaging Algorithms
Avoiding Shared Human Bias
What do we learn
Critical Velocity
Ring Size
Recovery N87
Recovery Sagittarius
Stochastic PD
Black hole simulation
Simple experiments
Optimal telescope design
Building confidence
Solving for the location of telescopes
Sensor Sampling Distribution
Core Design Problem
Applications
Technical Questions