The spatial resolution of hyperspectral images was generally low. As a result, a large number of mixed pixels existed. It brought some difficulties to target detection. In order to realize target detection in hyperspectral images under complex background, a target detection method based on de-endmember was proposed. On the basis of spectral de-mixing technology, the spectral mixing model under complex background was established and improved. The method of removing endpoints many times was adopted. The hyperspectral image after simplified background was obtained. The results show that, compared with the traditional RX target detection algorithm, the proposed algorithm can significantly improve the performance of target detection. In practical military applications, it provides a train of thought for target recognition and camouflage exposure of large-scale images.