Zhu, X., 2018. Optimization of intelligent fusion model for ship target image features in cloud computing environment. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 673–678. Coconut Creek (Florida), ISSN 0749-0208.

In the cloud computing environment, there is a problem that the accuracy of the image fusion of ship target image is low. Thus, an intelligent fusion model optimization method based on spatial features is proposed. The model utilizes a designed 6-layer convolution neural network to extract features of ship target image. Then, the feature selection method based on mutual information is used to sort ship target image eigenvectors in series according to importance, and the fixed-length eigenvectors are selected as the target recognition foundation based on the target image sharpness evaluation index. An intelligent fusion model based on spatial features is used to optimize the intelligent fusion model of ship target image features in cloud computing environment. Experimental results show that the fusion method proposed in this paper has high accuracy.