Ship recognition algorithm based on multi-level collaborative fusion of multi-source remote sensing images
The problem of serious speckle noise and poor visibility in polarimetric synthetic aperture radar(PolSAR)directly affect the accuracy of target recognition.A ship recognition algorithm based on the multi-level cooperative fusion of multi-source remote sensing images is proposed.The method of multi-level cooperative fusion is adopted to enrich the image features and improve the accuracy of ship recognition.Firstly,the multi-source remote sensing data is fused at the pixel level.Then,the feature-level fusion is carried out on the basis of the previous step.Finally,new target features are obtained.This method gives full play to the information complementarity advantage of PolSAR and multispectral images in different frequency bands.This method retains the polarization scattering characteristics of the target in different frequency bands of PolSAR.Meantime,the spectral-spatial information of multispectral data is also retained.Compared with the traditional single remote sensing data,the proposed method performs better in visibility and detection accuracy.The recognition accuracy of the proposed method is improved by 5.12％ at least.
万方数据
维普
