研究目的
Designing a target detection model that uses compressive measurements to find a sparse representation of image pixels from spectral information-based dictionaries and implementing an algorithm that determines whether the evaluated pixel is a target pixel.
研究成果
The proposed spectral image target detector achieves a performance similar to that of the target detection algorithms used in traditional spectral imaging, with a probability of detection of 98.92% if only 40% of the spectral information is used. A transmittance level between 10% and 30% produces the most accurate results.
研究不足
The main limitations include the mixture of spectral information with spatial information due to spectral shifting and the way in which the energy is integrated within the detector, and the number of spectral bands available is limited by the size of the detector.
