Object Characterization from Spectra Data
Abstract
In general, the task of identifying the shape, function, and status of objects from nonimaging temporally-resolved spectral data is impossible. This is due to the limited degrees of freedom in the data as compared to the degrees of freedom that define shape, function, and status. However, by modeling objects as combinations of simple shapes with simple reflective and spectral characteristics, the problem though daunting is expected to become tractable due to the reduction of degrees of freedom in object space. One anticipated result from this modeling process is that the properties of null and near-null object features can be characterized; that is, an object can be characterized as a set of observable features summed with null or near-null features that perturb the measurement only slightly or not at all. The initial development of classes presented in this paper is a first step towards an inversion procedure to map spectral data into classes.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2003
- Accession Number
- ADA423457
Entities
People
- Charles L. Matson
- Joshua Snodgrass
- K. K. Luu
- Kris Hamada
- S. M. Giffin
Organizations
- Air Force Research Laboratory