Comparative study of spectral matched filter, constrained energy minimization, and adaptive coherence estimator for subpixel target detection based on hyperspectral imaging

Abstract

This paper evaluates the detection performance of the three subpixel target detection algorithms based on the spectral signature of a target. Three subpixel target detection algorithms, Adaptive Coherence Estimator (ACE), Spectral Matched Filter (SMF), and Constrained Energy Minimization (CEM) are evaluated and compared using the Principal Component Analysis (PCA) spaced RIT Avon12 hyperspectral dataset. The performance of the three detectors is evaluated by generating the Receiver Operating Characteristic (ROC) curve. The ROC curves are generated by uploading the detection statistics image produced by the three detectors to the Data and Algorithm Standard Evaluation ( DASE) Website of IEEE Geoscience and Remote Sensing Society(GRSS) . Finally, we note the Area Under Curve (AUC) as the proposed utility metric value to evaluate the performance of the three detectors. The AUCs of the ROC curve produced by the ACE, CEM, and SMF are 94.0 %, 93.9 %, and 87.2 % respectively.