Paper
4 May 2006 Sample spectral correlation-based measures for subpixels and mixed pixels in real hyperspectral imagery
Author Affiliations +
Abstract
A hyperspectral imaging sensor images a scene using hundreds of contiguous spectral channels to uncover many substances that cannot be resolved by multspectral sensors with tens of discrete spectral channels. Many spectral measures used for target discrimination and identification in hyperspectral imagery have been derived directly from multsispectral imagery rather than from a hyperspectral imagery viewpoint. This paper demonstrates that on many occasions such spectral measures are generally not effective when it is applied to real hyperspectral data for discrimination and identification due to the fact that they do not take into account the very high sample spectral correlation (SSC) provided by hyperspectral sensors. In order to address this issue, two approaches, referred to as a priori sample spectral correlation (PR-SSC) and a posteriori SSC (PSSSC) are developed to account for spectral variability within real data to achieve better target discrimination and identification. While the former can be used to derive a family of a priori hyperspectral measures via orthogonal subspace projection (OSP) to eliminate interfering effects caused by undesired signatures, the latter results in a family of a posteriori hyperspectral measures that include sample covariance/correlation matrix as a posteriori information to increase ability in discrimination and identification. Interestingly, some well-known measures such as Euclidean distance (ED) and spectral angle mapper (SAM) can be shown to be special cases of the proposed PR-SSC and PS-SSC hyperspectral measures.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Weimin Liu and Chein-I Chang "Sample spectral correlation-based measures for subpixels and mixed pixels in real hyperspectral imagery", Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 62330J (4 May 2006); https://doi.org/10.1117/12.665285
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Hyperspectral imaging

Sensors

Distance measurement

Error analysis

Image processing

Databases

Algorithm development

Back to Top