Paper
17 June 1996 Toward automation of the extraction of lines of communication from multispectral images using a spatiospectral extraction technique
Author Affiliations +
Abstract
Adequate imagery for automated mapping of large areas became available with the successful launch of the 30-meter 7-band thematic mapper (TM) on Landsat 4 in 1982. Yet an adequate approach to automated line-of-communication (LOC) extraction continues to elude the remote sensing community. Perhaps the single biggest complicating factor is the inherently subpixel nature of the problem; almost all LOCs are narrower than current commercial sensor resolutions. Other complications include: spatial and temporal variability of LOC surface spectra, proximity to and abundance of spectrally similar materials, and atmospheric effects. We describe progress towards the detection and identification of LOCs using a technique that simultaneously extracts both spatial and spectral information. The approach currently uses a linear mixture model for simultaneously decomposing the image into fractional compositions and corresponding spectra using physical constraints. The algorithm differs from other approaches in that no traditional preprocessing or prior spatial or spectral information is required to extract the LOCs and their spectra. The algorithm has been successfully applied to TM and M-7 data. Results are presented.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Terrence H. Hemmer "Toward automation of the extraction of lines of communication from multispectral images using a spatiospectral extraction technique", Proc. SPIE 2758, Algorithms for Multispectral and Hyperspectral Imagery II, (17 June 1996); https://doi.org/10.1117/12.243208
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Lab on a chip

Multispectral imaging

Reflectivity

Earth observing sensors

Image processing

Image processing algorithms and systems

Image segmentation

Back to Top