In order to realize the ship target detection of the aerial reconnaissance image under complex environment with island and shore, a salient target detection method is proposed based on regional covariance and objectness. Under the saliency detection framework of conditional random field and dictionary learning, the sigma-features of each region are extracted and sparsely coded, and then the objectness feature is designed by using saliency optimization and the belief propagation algorithm is adopted to infer the saliency map of the ship target image, and finally the efficient subwindow search method is applied to achieve ship target detection. The experimental results show that the saliency map of the proposed method has complete target features and good background suppression, and it can achieve accurate target detection.