Assessment of noise reduction of hyperspectral imagery using a target detection application

This article presents an evaluation of a previously proposed noise reduction technique for hyperspectral imagery with regard to its use in remote sensing applications. Target detection from hyperspectral imagery was selected as an example for the evaluation. A hyperspectral datacube acquired using the airborne Shortwave Infrared Full Spectrum Imager (SFSI)-II with man-made targets deployed in the scene of the datacube was tested. In addition to an evaluation using the receiver operating characteristic (ROC) curve approach, we used a spectral unmixing technique to generate the fraction images of the target materials, measured the area of the targets derived from the datacube before and after applying the noise reduction technology, and then compared the derived target areas to the real targets to assess the detectability of the targets. The area ratio between a derived target and the real target was used as the criterion in the evaluation. The evaluation results show that the noise reduction technique can help to better serve remote sensing applications. The small targets that cannot be detected from the original datacube were detected after the noise reduction using the technology.