Dynamic hyperspectral imaging

Marina V. A. Murzina; J. Paul Farrell

doi:10.1117/12.598620

9 May 2005 Dynamic hyperspectral imaging

Marina V. A. Murzina, J. Paul Farrell

Proceedings Volume 5769, Nondestructive Detection and Measurement for Homeland Security III; (2005) https://doi.org/10.1117/12.598620
Event: Nondestructive Evaluation for Health Monitoring and Diagnostics, 2005, San Diego, CA, United States

Abstract

Bad things often happen fast. This means that we need to react fast. In this work, we develop the technology that allows one to identify and characterize fast events. In real time, we dynamically process hyperspectral information of a scene, specifically analyzing its temporal behavior. The goal is to detect fast and super-fast events like explosions, fast-moving objects and instant changes in the chemical composition of air and other materials. Until recently, the enormous quantity of hyperspectral information confined us to static hyperspectral data processing. Hyperspectral techniques were used for finding certain objects, chemicals, or anomalies in a picture, frame by frame, statically. Dynamic (temporal) analysis was developed primarily for astrophysical applications performed a long time after the frames had been captured. In this work, we study ways of taking advantage of emerging hardware technologies that allow one to look at hyperspectral information dynamically: by characterizing temporal changes as they occur. We apply methods from astrophysics (supernova observations) and present our unique algorithms for contemporaneous dynamical analysis of hyperspectral data. The application addresses the question: have there been any sudden changes in the hyperspectral pattern of a scene? If there were sudden changes, were those changes related to a substantial energy release? These questions do not depend on assumptions about specific spectral patterns, chemical composition, or shapes: we look for any changes in a scene. Such dynamical analysis can therefore allow one to react promptly to fast events without prior knowledge about what occurred. This paper addresses issues specific to dynamic (as opposed to static) hyperspectral imaging, algorithmic approaches to dynamic hyperspectral data processing, and associated hardware-implementation issues.

Citation Download Citation

Marina V. A. Murzina and J. Paul Farrell "Dynamic hyperspectral imaging", Proc. SPIE 5769, Nondestructive Detection and Measurement for Homeland Security III, (9 May 2005); https://doi.org/10.1117/12.598620

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