Does virtual dimensionality work in hyperspectral images?

Peter Bajorski

doi:10.1117/12.818172

27 April 2009 Does virtual dimensionality work in hyperspectral images?

Peter Bajorski

Proceedings Volume 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV; 73341J (2009) https://doi.org/10.1117/12.818172
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

The effective dimensionality (ED) of hyperspectral images is often viewed as the dimensionality of an affine subspace defined by linear combinations of spectra of materials present in the image. That affine subspace is expected to give an acceptable approximation to all pixels. At this point, there is no precise definition of ED. In an effort to assess ED, a notion of virtual dimensionality (VD) has been developed, and it is being used in many papers including those published in TGARS. The ever- spreading use of VD warrants its thorough investigation. In this paper, we investigate properties of VD, and we show that VD largely depends on the average value of all spectra rather than on ED. We show specific examples when VD would give entirely misleading results. We also explain fallacies associated with justifications for VD.

Citation Download Citation

Peter Bajorski "Does virtual dimensionality work in hyperspectral images?", Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 73341J (27 April 2009); https://doi.org/10.1117/12.818172

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