Comprehensive Space-Object Characterization using Spectrally Compressive Polarimetric Sensing

Abstract

Among the most important accomplishments of the project are 1. Development of physical models that predict how surface roughness, texture, and shape alter the state of polarization of solar illumination scattered/reflected by a space object and their use to determine surface shape, material composition, and texture; 2. Derivation and application of a number of approximate, task-based theoretical performance-assessment tools based on statistical information and Bayesian error analysis that are numerically efficient and generally applicable to image analysis, recovery, and reconstruction tasks; 3. Design, fabrication, and testing of two polarimetrically enhanced versions of the CASSI instrument using polarization sensitive elements; 4. Development and benchmarking of new algorithms for highly resolved spatial segmentation, material identification, shape determination, surface characterization, and extraction of rigid-body kinematics from polarimetric CASSI data; and 5. Recovery of 3D shape, rigid-body kinematics, and surface characterization from a time series of 2D compressive spectral-polarimetric images.

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Document Details

Document Type
Technical Report
Publication Date
Apr 08, 2015
Accession Number
ADA622415

Entities

People

  • David Brady
  • Robert Plemmons
  • Sudhakar Prasad

Organizations

  • University of New Mexico

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms
  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Amplitude Modulation
  • Compressed Sensing
  • Detectors
  • Error Analysis
  • Identification
  • Information Processing
  • Materials
  • Measurement
  • Modulation
  • Modulators
  • Optical Phenomena
  • Optics
  • Polarization
  • Refraction
  • Refractive Index
  • Space Objects

Readers

  • Computer Vision.
  • Image Processing and Computer Vision.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • Space