Hybrid Fusion-Based Background Segmentation in Multispectral Polarimetric Imagery

Robust Materials Classification Based on Multispectral Polarimetric BRDF Imagery

When light is reflected from object surface, its spectral characteristics will be affected by surface’s elemental composition, while its polarimetric characteristics will be determined by the surface’s orientation, roughness and conductance. Multispectral polarimetric imaging technique records both the spectral and polarimetric characteristics of the light, and adds dimensions to the spatial in...

Polarimetric Segmentation of Synthetic Aperture Radar Imagery

This paper considers the problem of clutter segmentation in fully polarimetric, high resolution, synthetic aperture radar (SAR) imagery. The goal of segmentation is to partition an image into regions of homogeneous terrain types (grass regions, tree regions, roads, etc.). Three approaches to segmentation are examined: (1) the optimal polarimetric classifier, (2) the optimal normalized polarimet...

Topological Anomaly Detection Performance with Multispectral Polarimetric Imagery

Polarimetric imaging has demonstrated utility for increasing contrast of manmade targets above natural background clutter. Manual detection of manmade targets in multispectral polarimetric imagery can be challenging and a subjective process for large datasets. Analyst exploitation may be improved utilizing conventional anomaly detection algorithms such as RX. In this paper we examine the perfor...

Enhancement of Target Contrast in Polarimetric Imagery Using Image Fusion

Object separation by polarimetric and spectral imagery fusion

When light is reflected from object surface, its spectral characteristics will be affected by the surface’s elemental composition, and its polarimetric characteristics will be governed by the surface’s roughness and conductance. Polarimetric and multispectral imaging can provide complementary discriminative information in applications such as object separation. However, few methods have been pr...