V. Paul Pauca - Imaging Research


Recent Research Projects

Statistical Image Analysis and Applications to 3D Imaging for Improved SSA

  1. This project is devoted to the study of statistical methods of performance assessment of SSA systems that rely on optical and IR imaging and associated technologies. We focus on two critical applications: 1) the assessments of space-object surface integrity, 3D shape, and material composition via ground-based polarimetric and spectral solar-reflectance (BRDF) measurements; and 2) space-based 3D localization and tracking of space debris via rotating PSF imaging. The PI for this project is Prof. Sudhakar Prasad in the University of New Mexico.

  1. Sponsored by the Air Force Office of Scientific Research

Analytics of Acoustic Emissions Data

  1. Stress due to mechanical loads and other factors can significantly damage the internal structure of composite materials, such as those used in modern aircraft fuselage.  The main goal of this project is to develop methods to classify various types of damage, such as matrix cracking and fiber failure, from acoustic signals emitted by the composite material.

  1. Sponsored by The Boeing Company

Methods for Fusion and Compression of LiDAR and Hyperspectral Data

  1. LADAR and hyperspectral image data offer a vast amount of information that can completely reconstruct surfaces and generate reflections.  The main goals of this project are to develop effective methods for compression of LiDAR and hyperspectral data, while enabling accurate object and target recognition from the data ensemble. The project also involves significant collaboration with researchers at The Boeing Company, Seattle, WA.

  1. Sponsored in part by Boeing and the National Geospatial-Intelligence Agency

Challenging Ocular Image Recognition 

  1. The main objective of this project is to develop new exploitation and analysis methods for ocular recognition to deliver robust performance under challenging imaging conditions. The team involves researchers from Carnegie Mellon University, West Virginia University and Wake Forest University.

  1. Sponsored in part by the Intelligence Advanced Research Projects Activity


  1. BulletSaurabh Morchhale, M.S. ’16

  2. BulletRongzhong Li, M.S. ’16

  3. BulletMichael Forkin, M.S. ’11

  4. BulletMatt Steen, B.S. ’10

  5. BulletSebastian Berisha, M.S. ’10

  6. BulletXiao Xu, M.S. ’10

  7. BulletBrian Gray, M.S. ’08

  8. BulletSantiago Saldana, M.S. ’08

  9. BulletRyan Barnard, M.S. ’07

  10. BulletEmily Leonhardt, B.S. ’06

  11. BulletDaniel Fan, M.S. ’06

  12. BulletJon Piper, ’04

Student Theses & Recent Publications

  1. BulletQ. Zhang, P. Pauca and R. Plemmons. “Detecting Objects under Shadows by Fusion of Hyperspectral and LiDAR Data: A Physical Model Approach,” 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013.

  2. BulletQ. Zhang, P. Pauca and R. Plemmons. “Randomized Methods in Lossless Compression of Hyperspectral Data,” to appear in the Journal of Applied Remote Sensing, 2013.

  3. BulletD. Nikic, P. Pauca, R. Plemmons J. Wu, P. Zhang. A Novel Approach To Environment Reconstruction In LIDAR and HSI Datasets. AMOS Conference, Maui, HI, Sept. 2012.

  4. BulletA. Ross, R. Jillela, J. Smereka, V. N. Boddeti, B. V. K. VijayaKumar, R. Barnard, X. Hu, P. Pauca, R. Plemmons, "Matching Highly Non-ideal Ocular Images: An Information Fusion Approach," Proc. of the 5th IAPR International Conference on Biometrics (ICB), (New Delhi, India), March/April 2012.

  5. BulletR. Jillela, A. Ross, V. N. Boddeti, B. V. K. VijayaKumar, X. Hu, R. Plemmons, P. Pauca, "An Evaluation of Iris Segmentation Algorithms in Challenging Periocular Images", in Handbook of Iris Recognition, K. Bowyer and M. Burge (Eds.), Springer 2012.

  6. BulletX. Hu, P. Pauca and R. Plemmons. Iterative Directional Ray-based Iris Segmentation for Challenging Periocular Images Preprint September, 2011, Published in Biometric Recognition, December 2011, LNCS7098, Springer.

  7. Bullet[PDF] V. P. Pauca, M. Forkin, X. Xu, Robert Plemmons and Arun Ross. Challenging Ocular Image Recognition. In Biometric Technology for Human Identification VIII, Proc. of SPIE, Vol. 8029 80291V-1 – 80291V-13, Orlando, FL, April 2011.


Major directions

We are interested in developing imaging algorithms capable of rapidly and accurately characterizing features of interest, while dealing with blurry, noisy, and incomplete data. The main goal is to improve performance by exploiting the rich information available from multi-modal data as well as prior knowledge about the task at hand.