In order to solve the problems of low saliency value of the ships whose color are similar to sea surface color,and background interference such as coastlines and islands,a remote sensing ship detection algorithm based on ship saliency in candidate regions is proposed.The improved Frequency Tuning (FT) saliency detection and edge detection of Hessian matrix are used to obtain two types of saliency maps,which are then fused by using Pulse Coupled Neural Network (PCNN) to obtain the comprehensive saliency map,so as to improve the saliency value of the ships whose color are similar to the color of sea surface background,thus extracting effective ship slices of candidate regions.Then,the migration VGG16 network is used to extract the features of the dataset and train SoftMax classifier,so as to identify the slices of the candidate region and separate the possible background interference in the candidate region,thus realizing ship target detection.The experimental results show that the proposed algorithm has good accuracy.