On the performance of CEM and TCIMF

Detection of targets at subpixel level is a very challenging task due to the lack of available spatial properties, low probability of target occurrence, and background interference. Constrained Energy Minimization (CEM) is a popular technique for target detection in hyperspectral images. It is particular useful when only the desired target signature is available. When those undesired signatures to be eliminated are also known, Target Constrained Interference Minimization Filter (TCIMF) can be used to minimize the output of undesired signatures to further improve the target discrimination performance. Both CEM and TCIMF are match-filter based detectors. In this paper, we will further investigate their performance in background suppression, and how to improve the generalization capability in the detection of objects with large size.