ATTENTION: We're pleased to announce that EI 2021 will be fully online! We recognize that one of the most important features of attending EI is interacting with colleagues from Industry and Academia. We are committed to making community connection a priority and to providing ample opportunities to meet and discuss personally with others. We see the move to an online platform as an opportunity for greater numbers of people to join from around the world. Join us on this exciting adventure . . . submit your work today!
Conference Overview
More than ever before, computers and computation are critical to the image formation process. Across diverse applications and fields, remarkably similar imaging problems appear, requiring sophisticated mathematical, statistical, and algorithmic tools. This conference focuses on imaging as a marriage of computation with physical devices. It emphasizes the interplay between mathematical theory, physical models, and computational algorithms that enable effective current and future imaging systems. Contributions to the conference are solicited on topics ranging from fundamental theoretical advances to detailed system-level implementations and case studies.
2021 Conference Topics
Algorithms and methodologies
- Inverse methods
- Model-based imaging and compressed sensing
- Estimation techniques
- Imaging system modeling and simulation
- Optimization approaches
- Multiscale image processing and modeling
- Statistical learning and analysis methods
Key problem areas
- Image recovery from sensor data
- Denoising, demosaicing, color correction
- Deblurring and high-resolution rendering
- Image and color transforms and analysis
- Visual perception as an inverse problem
- Tomography, transmission, and emission
- Microscopy, light, EM, and non-classical
- Optical coherence imaging
- MRI, anatomical, functional, and molecular
- Acoustic imaging
- Diffusion optical imaging
- Electrical resistance and impedance imaging
- Crystallography
- Synthetic aperture radar
- Holographic and coherent optical imaging
- Computational depth-of-field enhancement
- Intelligent image cropping and scaling
- Plenoptics and non-classical image capture
- Coded aperture and compressed sensing
Current and future applications
- Consumer imaging and computational photography
- Super-resolution and enhancement
- Imaging and camera networks
- Non-destructive evaluation for additive manufacturing
- Medical imaging and image-guided surgery
- Microscopy and clinical applications
- Emerging biomedical applications
- Geophysical imaging
- Materials imaging and characterization
- Nondestructive testing and evaluation
- Imagery-based surveillance and tracking
- Target classification and identification
- Remote sensing applications
2021 Special Sessions
For Computational Imaging XIX, submissions are particularly encouraged for the planned sessions on AI-driven imaging instruments, turbulent and scattering mediums, and autonomous materials research.
AI-driven Imaging Instruments
Session Organizing Chairs:
Doga Gursoy, Argonne National Laboratory (United States)
Ulugbek S Kamilov, Washington University in St. Louis (United States)
Singanallur V Venkatakrishnan, Oak Ridge National Laboratory (United States)
Recent advances in machine-learning (ML) and artificial intelligence (AI) have sparked new lines of research on integrating AI/ML techniques for computational imaging systems. This special session will bring together researchers developing algorithms and systems for a variety of applications in which AI/ML techniques are enabling dramatic improvements in overall performance. Potential applications include (but not limited to) optical microscopy, scientific microscopy and tomography (electrons, X-rays, neutrons etc.), medical imaging systems, and transportation security systems.
Imaging through Turbulent & Scattering Mediums
Session Organizing Chair:
Casey Pellizzari, United States Air Force Academy (United States)
In many imaging applications, light from an object passes through turbulent or scattering mediums. These mediums cause unwanted phase and amplitude variations in the signal, resulting in distorted images. Computational methods play a key role in correcting these distortions. This session explores how such computational methods are being used to push the boundaries of imaging through turbulent and scattering mediums. Example topic areas include imaging through atmospheric turbulence, imaging through fog, smoke, haze, etc., imaging through tissue, and imaging through water. Both passive and active methods are welcome.
In Situ Sensing and Analysis for Autonomous Materials Research
Session Organizing Chairs:
Benji Maruyama, Air Force Research Laboratory (AFRL) (United States)
Chiwoo Park, Florida A&M University-Florida State University College of Engineering (United States)
Kristofer Reyes, University at Buffalo (United States)
The materials community has worked to improve the rate of research progress by developing autonomous research systems that use advanced decision algorithms to plan, execute, and complete campaigns of materials experiments iteratively. For automating the necessary data collection from the closed loop systems system, the integration of in situ metrology to the system is essential. This special session highlights recent developments in in situ metrology for materials research and related real time data analysis. Example topics include in situ electron microscopy, scanning probe microscopy, tomography, image superresolution, adaptive and compressive imaging, and related image BIGDATA techniques.
Software for Computational Imaging: Open Source Tools and Best Practices
Session Organizing Chair:
Brendt Wohlberg, Los Alamos National Laboratory (United States)
Luke Pfister, Los Alamos National Laboratory (United States)
The goal of the first part of this session will be to introduce the audience to some of the leading open source projects with relevance to computational imaging. It will feature talks by members of the development teams of each of the projects in question. The second part of the session will be more tutorial in nature, providing an overview of best practices in software development, with a focus on the development of reliable and well documented software that can make a long-term contribution to the community.
Computational Imaging for Materials Applications
Session Organizing Chairs:
Jeff Simmons, Air Force Research Laboratory (Materials and Manufacturing Directorate) (United States)
Mary Comer, Purdue University (United States)
Begum Gulsoy, Northwestern University (United States)
Materials science and microscopy have always been intimately linked, with the major connection being the use of microstructure as a means of controlling processing and properties. Being steeped in physics and other hard sciences, the field traditionally has worked with forward modeling and is now benefiting from modern inversion methods, as are commonly used in computational imaging. This symposium highlights recent advances in materials science as a direct consequence of cross-disciplinary approaches between computational imaging and materials science. This symposium covers, but is not limited to segmentation, learning approaches, forward modeling of material-probe-detector interactions, data fusion, anomaly detection, denoising, detection and tracking, and superresolution.
Committee
2021 Program Chairs
Charles A. Bouman, Purdue University (United States)
Gregery T. Buzzard, Purdue University (United States)
Robert L. Stevenson, University of Notre Dame (United States)
Program Committee
Clem Karl, Boston University (United States)
Eric Miller, Tufts University (United States)
Joseph A O'Sullivan, Washington University in St. Louis (United States)
Hector J Santos-Villalobos, Oak Ridge National Laboratory (United States)
Ken D. Sauer, University of Notre Dame (United States)
Community Chair
Begum Gulsoy, Northwestern University (United States)