A band selection approach for small target detection based on CEM

Constrained energy minimization (CEM) is one of the most widely used target detection methods due to its simplicity and effectiveness. From a mathematical perspective, the detection result can be regarded as the summation of bands weighted by the corresponding components of the CEM operator. Based on this point of view, we propose a supervised band selection idea for CEM target detection. Three different band selection methods for CEM (namely, BSC1, BSC2 and BSC3) are presented and compared. Some comparative experiments based on real hyperspectral data are conducted to evaluate the performance of these methods (the presented and other two methods). The results show that BSC3 is the most effective band selection method. The CEM detection result is quite acceptable using only a few of the bands selected by BSC3. BSC1 and BSC2 are also more accurate than other compared band selection methods when the number of selected bands is relatively large (>18 in our experiments).