Proceedings Article | 13 May 2010
Proc. SPIE. 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI
KEYWORDS: Target detection, Image fusion, Detection and tracking algorithms, Polarization, Sensors, Pattern recognition, Reflectivity, Target recognition, Hyperspectral target detection, Data fusion
Pattern recognition deals with the detection and identification of a specific target in an unknown input scene. Target
features such as shape, color, surface dynamics, and material characteristics are common target attributes used for
identification and detection purposes. Pattern recognition using multispectral (MS), hyperspectral (HS), and polarization-based
spectral (PS) imaging can be effectively exploited to highlight one or more of these attributes for more efficient
target identification and detection. In general, pattern recognition involves two steps: gathering target information from
sensor data and identifying and detecting the desired target from sensor data in the presence of noise, clutter, and other
artifacts. Multispectral and hyperspectral imaging (MSI/HSI) provide both spectral and spatial information about the
target. As the reflection or emission spectral signatures depend on the elemental composition of objects residing within
the scene, the polarization state of radiation is sensitive to the surface features such as relative smoothness or roughness,
surface material, shapes and edges, etc. Therefore, polarization information imparted by surface reflections of the target
yields unique and discriminatory signatures which could be used to augment spectral target detection techniques, through
the fusion of sensor data. Sensor data fusion is currently being used to effectively recognize and detect one or more of
the target attributes. However, variations between sensors and temporal changes within sensors can introduce noise in the
measurements, contributing to additional target variability that hinders the detection process. This paper provides a quick
overview of target identification and detection using MSI/HSI, highlighting the advantages and disadvantages of each. It
then discusses the effectiveness of using polarization-based imaging in highlighting some of the target attributes at single
and multiple spectral bands using polarization spectral imaging (PSI), known as spectropolarimetry imaging.
