The invention discloses a superpixel local information measurement-based polarized SAR ship target detection method, and mainly aims at solving the problem that the target detection rate lower complicated scenes is low. The method comprises the following steps of: 1, carrying out superpixel segmentation on an original image so as to obtain superpixel segmentation results under different scales; 2,for the segmented results, calculating three superpixel level-based difference measurements by utilizing a sliding window model; 3, converting the superpixel level-based difference measurements intopixel level-based difference measurements; 4, mapping pixel-level difference measurement vectors into different measurement values by utilizing kernel fisher discrimination, so as to a difference measurement value of each pixel point; and 5, classifying the difference measurement values of the pixel points by utilizing a linear SVM classifier, determining a category of each pixel and carrying outautomatic target detection. The method is capable of enhancing the target detection performance under complicated scenes an realizing the automatic detection process, and can be used for subsequent ship target discrimination, recognition and classification.