Development and comparison of data reconstruction methods for chromotomographic hyperspectral imagers

Michael R. Hawks; Alan Jennings; Ryan Tervo

doi:10.1117/12.2178139

21 May 2015 Development and comparison of data reconstruction methods for chromotomographic hyperspectral imagers

Michael R. Hawks, Alan Jennings, Ryan Tervo

Proceedings Volume 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI; 94720G (2015) https://doi.org/10.1117/12.2178139
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

Chromotomography is a form of hyperspectral imaging that uses a prism to simultaneously record spectral and spatial information, like a slitless spectrometer. The prism is rotated to provide multiple projections of the 3D data cube on the 2D detector array. Tomographic reconstruction methods are then used to estimate the hyperspectral data cube from the projections. This type of system can collect hyperspectral imagery from fast transient events, but suffers from reconstruction artifacts due to the limited-angle problem. Several algorithms have been proposed in the literature to improve reconstruction, including filtered backprojection, projection onto convex sets, subspace constraint, and split- Bregman iteration. Here we present the first direct comparison of multiple methods against a variety of simulatedtargets. Results are compared based on both image quality and spectral accuracy of the reconstruction, where previous literature has emphasized imaging only. In addition, new algorithms and HSI quality metrics are proposed. We find the quality of the results depend strongly on the spatial and spectral content of the scene, and no single algorithm is consistently superior over a broad range of scenes.

Citation Download Citation

Michael R. Hawks, Alan Jennings, and Ryan Tervo "Development and comparison of data reconstruction methods for chromotomographic hyperspectral imagers", Proc. SPIE 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI, 94720G (21 May 2015); https://doi.org/10.1117/12.2178139

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
12 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Reconstruction algorithms

Image quality

Hyperspectral imaging

Detection and tracking algorithms

Prisms

Head

Imaging systems

Show All Keywords

Keywords/Phrases

Search In:

Publication Years