Based on the characteristics of the FY-3 MERSI II images， an algorithm of independent sea ice segmentation based on U-ASPP-Net is proposed. The algorithm introduces the Atrous Spatial Pyramid Pooling module and Atrous Depthwise Separable Convolution on the basis of U –Net to develop a new independent sea ice segmentation network U-ASPP-Net. Meanwhile， FDWloss is used as the loss function at the back end of the network. Finally， the overlap elimination strategy is used to generate the final independent sea ice segmentation map. In order to verify the accuracy and effectiveness of U-ASPP-Net， U-Net， Deeplab v3+ and partition gradient difference and bimodal threshold segmentation method are selected as control methods for experiments. The experimental results show that the independent sea-ice fine segmentation method based on U-ASPP-NET is superior to the other methods in the four indexes of OA， Kappa coefficient， IOU， Dice coefficient. It has a strong ability to extract details and edges， and has a high degree of reduction to tiny sea ice. In addition， this algorithm can solve the problem of thin cloud interference that cannot be solved when extracting independent sea ice based on medium-resolution remote sensing images to a certain extent. It still has a good ability to extract sea ice under thin clouds and can provide more accurate technical support for the dynamic planning of the Arctic route.