Hyperspectral Target Detection : An Overview of Current and Future Challenges

Abstract

Over the last decade, hyperspectral imagery (HSI) obtained by remote sensing systems has provided significant information about the spectral characteristics of the materials in the scene. Typically, a hyperspectral spectrometer provides hundreds of narrow contiguous bands over a wide range of the electromagnetic spectrum. Hyperspectral sensors measure the reflective (or emissive) properties of objects in the visible and short-wave infrared (IR) regions (or the mid-wave and long-wave IR regions) of the spectrum. Processing of these data allows algorithms to detect and identify targets of interest in a hyperspectral scene by exploiting the spectral signatures of the materials [1], [2].