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Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
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Higher-order computational model for coded aperture spectral imaging.

Henry Arguello1, Hoover Rueda, Yuehao Wu

  • 1Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware 19716, USA.

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|April 3, 2013
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Summary
This summary is machine-generated.

This study introduces a more precise computational model for coded aperture snapshot spectral imaging (CASSI) systems. This enhanced model improves image reconstruction quality and reduces reliance on system calibration.

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Area of Science:

  • Optics and Photonics
  • Computational Imaging
  • Remote Sensing

Background:

  • Coded aperture snapshot spectral imaging (CASSI) systems capture 3D spatio-spectral data using a single 2D snapshot.
  • Current CASSI models approximate sensing as summed, shifted spectral voxels, requiring calibration.
  • This approximation can limit reconstruction accuracy and system flexibility.

Purpose of the Study:

  • To develop a higher-order precision model for optical sensing in CASSI.
  • To improve image reconstruction quality and reduce calibration dependency.
  • To enhance suitability for advanced CASSI configurations like multiframe systems.

Main Methods:

  • Developed a higher-order precision model for CASSI optical sensing.
  • Incorporated a more accurate discretization of underlying spectral signals.
  • Validated the model through simulations and experimental measurements.

Main Results:

  • The new model yields image reconstructions less dependent on calibration.
  • Achieved improved image quality compared to traditional CASSI models.
  • Demonstrated suitability for reconfigurable multiframe CASSI systems.

Conclusions:

  • The proposed higher-order precision model offers significant advantages for CASSI systems.
  • Accurate signal discretization is key to reducing calibration needs and enhancing reconstruction.
  • This model advances the capabilities of snapshot spectral imaging technologies.