Because the boundary pixels are easy to be classified as a background in the multi ship target detecting processing, this paper proposes a multi-ship saliency detection method based on patch fusion by color clustering. Firstly, this method detects the color similarity of the pixels in the neighbourhood, and the adjacent pixels with the similar color are gathered as an image patches. Then, the image patches are expanded to make them include some pixels of other patches, so as to enhance the contrast value of the pixels of patches. Then, edge pixels are marked in the background index to calculate the saliency ability of the pixels in image patches and the threshold segmentation method is used to obtain the saliency region of the target. As the image patches have the features of partial overlap, the weight values are used to fuse the saliency images with the partial overlaps, so that the saliency detection results on a whole image for the multi-ship targets are obtained. The experimental tests are carried out for the multi-ship target images, and the results from the proposed algorithm in this paper and the current advanced detection algorithms are compared. The results show that the proposed method based on patch fusion by color clustering has the recall rate more than 78%, the accurate above 92%, and its comprehensive evaluation index Fβ is more than 0.7. Both for comparisons of the single index or the entire indexes in this experiments, the algorithm is superior to other methods.