Joint segmentation and reconstruction of hyperspectral data with compressed measurements.
This work describes numerical methods for the joint reconstruction and segmentation of spectral images taken by compressive sensing coded aperture snapshot spectral imagers (CASSI). In a snapshot, a CASSI captures a two-dimensional (2D) array of measurements that is an encoded representation of both spectral information and 2D spatial information of a scene, resulting in significant savings in acquisition time and data storage. The reconstruction process decodes the 2D measurements to render a three-dimensional spatio-spectral estimate of the scene and is therefore an indispensable component of the spectral imager. In this study, we seek a particular form of the compressed sensing solution that assumes spectrally homogeneous segments in the two spatial dimensions, and greatly reduces the number of unknowns, often turning the underdetermined reconstruction problem into one that is overdetermined. Numerical tests are reported on both simulated and real data representing compressed measurements.
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Related Subject Headings
- Optics
- Optical Phenomena
- Imaging, Three-Dimensional
- Image Processing, Computer-Assisted
- Data Compression
- 5102 Atomic, molecular and optical physics
- 4008 Electrical engineering
- 0913 Mechanical Engineering
- 0906 Electrical and Electronic Engineering
- 0205 Optical Physics
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Optics
- Optical Phenomena
- Imaging, Three-Dimensional
- Image Processing, Computer-Assisted
- Data Compression
- 5102 Atomic, molecular and optical physics
- 4008 Electrical engineering
- 0913 Mechanical Engineering
- 0906 Electrical and Electronic Engineering
- 0205 Optical Physics