Paper
3 May 2006 Material classification based on multi-band polarimetric images fusion
Yongqiang Zhao, Quan Pan, Hongcai Zhang
Author Affiliations +
Abstract
Polarization imparted by surface reflections contains unique and discriminatory signatures which may augment spectral target-detection techniques. With the development of multi-band polarization imaging technology, it is becoming more and more important on how to integrate polarimetric, spatial and spectral information to improve target discrimination. In this study, investigations were performed on combining multi-band polarimetric images through false color mapping and wavelet integrated image fusion method. The objective of this effort was to extend the investigation of the use of polarized light to target detection and material classification. As there is great variation in polarization in and between each of the bandpasses, and this variation is comparable to the magnitude of the variation intensity. At the same time, the contrast in polarization is greater than for intensity, and that polarization contrast increases as intensity contrast decreases. It is also pointed out that chromaticity can be used to make targets stand out more clearly against background, and material can be divided into conductor and nonconductor through polarization information. So, through false color mapping, the difference part of polarimetric information between each of the bandpasses and common part of polarimetric information in each of the bandpasses are combined, in the resulting image the conductor and nonconductor are assigned different color. Then panchromatic polarimetric images are fused with resulting image through wavelet decomposition, the final fused image have more detail information and more easy identification. This study demonstrated, using digital image data collected by imaging spectropolarimeter, multi-band imaging polarimetry is likely to provide an advantage in target detection and material classification.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yongqiang Zhao, Quan Pan, and Hongcai Zhang "Material classification based on multi-band polarimetric images fusion", Proc. SPIE 6240, Polarization: Measurement, Analysis, and Remote Sensing VII, 624007 (3 May 2006); https://doi.org/10.1117/12.665456
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CITATIONS
Cited by 9 scholarly publications.
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KEYWORDS
Image fusion

Polarimetry

Wavelets

Dielectric polarization

Polarization

Associative arrays

Image classification

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