Paper
17 June 1996 Adaptive multispectral normalization system
Mary R. Lawler-Covell, Karen F. West, Michael W. Kiefer, Sarah M. Officer, Michael J. Price
Author Affiliations +
Abstract
A multispectral normalization processing system has been developed to produce percent reflectance maps from multispectral imagery (MSI) in the .4 to 2.5 micron wavelength range. It is adaptive to multiple spatial resolutions, supporting resolutions in the .25 meter to 30 meter range. The normalization process takes advantage of known naturally occurring and man-made materials in the image to remove the effects of atmospheric haze and sensor gain contributions for each multispectral band. The output product is a percent reflectance map for each multispectral band. Although the normalization technique is well known, the MSI normalization system (MSINS) provides a simple, adaptive, robust graphical user interface for normalizing multispectral imagery from various sensor platforms. Over 130 different surface material spectra have been collected from reputable sources in literature and other spectral material libraries and installed in the MSINS Materials Spectral Information Database (MSID). The MSID has been designed to allow the addition of new material spectra into the system via a menu interface. A neural-net-based region grower has been developed to minimize user interaction and increase the robustness and repeatability of the normalization. New multispectral sensor platforms can be introduced into the system quickly via a menu interface. The current system was developed and tested using Landsat Thematic Mapper, Erim M7 Mapper, Positive Systems ADAR 5500, and ITRES casi multispectral imagery.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mary R. Lawler-Covell, Karen F. West, Michael W. Kiefer, Sarah M. Officer, and Michael J. Price "Adaptive multispectral normalization system", Proc. SPIE 2758, Algorithms for Multispectral and Hyperspectral Imagery II, (17 June 1996); https://doi.org/10.1117/12.243221
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KEYWORDS
Multispectral imaging

Sensors

Reflectivity

Image processing

Spatial resolution

Databases

Earth observing sensors

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