ing at the problems of low accuracy and high false alarm rate caused by artificial targets in the process of optical remote sensing image docked ship detection. This paper proposes a new method based on edge line gradient features and aggregation channel features for docked ship detection. The multi-structural and multiscale element morphological filters are used to realize the division of sea and land. According to the rectangular shape characteristics of the port in remote sensing images, the edge gradient tangent angle and the port concave and convex features are defined to locate the port,obtaining collection of port region of interest. The aggregation channel features of ships will be extracted and used to train the classifier for the docked ships by AdaBoost algorithm. The trained classifier is used to confirm the real ships in the port. Compared with traditional HOG feature and Haar feature, the proposed algorithm has better detection effect, and its precision and recall rate are greatly improved.