<title>Subpixel object detection using hyperspectral imaging for search and rescue operations</title>

Abstract

Time critical search & rescue (s&r) operations often requires the detection of small objects in a vast area. While an airborne search can cover the area, no operational instrumental tools currently exist to actually replace the human operator. By producing the spectral signature of each pixel in a spatial image, multi- and hyper-spectral imaging (HSI) sensors provides a powerful capability for automated detection of subpixel size objects that are otherwise unresolved objects in conventional imagery. This property of HSI naturally lends itself to s&r operations. A lost hiker, skier, life raft adrift in the ocean, downed pilot or small aircraft wreckage targets, can be detected from relatively high altitude based on their unique spectral signatures. Moreover, the spectral information obtained allows the search craft to operate at substantially reduced spatial resolution thereby increasing scene coverage without a significant loss in detection sensitivity. The paper demonstrates the detection of objects as small as 1/10 of an image pixel from a sensor flying at over 6 km altitude. A subpixel object detection algorithm using HSI, based on local image statistics without reliance on spectral libraries is presented. The technique is amenable to fast signal processing and the requisite hardware can be built using inexpensive off the shelf technology. This makes HSI a highly attractive tool for real-time, autonomous instrument-based implementation. It can complement current visual-based s&r operations or emerging synthetic aperture radar sensors that are much more expensive.