基于CNN和Transformer聚合的遥感图像超分辨率重建

胡明志,孙俊,杨彪,常开荣,杨俊龙

Super-resolution reconstruction of remote sensing image based on CNN and Transformer aggregation

Mingzhi HU,Jun SUN,Biao YANG,Kairong CHANG,Junlong YANG

表 1 AID测试数据集6个随机场景下不同模型的PSNR和SSIM指标

Tab.1 PSNR and SSIM metrics of different models on six randomly selected scenes from AID test dataset

模型 飞机场 城市 农田 停车场 运动场 港口 PSNR/dB SSIM PSNR/dB SSIM PSNR/dB SSIM PSNR/dB SSIM PSNR/dB SSIM PSNR/dB SSIM Bicubic 26.22 0.6871 23.73 0.6182 29.49 0.7347 19.73 0.5451 25.45 0.6905 22.23 0.6699 Swinir 24.43 0.6598 22.19 0.5867 28.15 0.7142 17.79 0.5126 24.20 0.6666 20.09 0.6401 CDC 24.82 0.6272 22.50 0.5867 26.87 0.6601 20.04 0.5547 24.11 0.6550 21.71 0.6691 DAN 25.70 0.6922 23.60 0.6277 28.75 0.7307 19.72 0.5711 25.31 0.6960 21.45 0.6682 real-Esrgan 27.81 0.7296 24.82 0.6768 30.20 0.7664 21.06 0.6468 26.33 0.7338 22.84 0.7316 BSRGAN 27.74 0.7318 25.24 0.6754 30.80 0.7704 21.79 0.6413 27.10 0.7351 23.57 0.7328 MM-realSR 27.83 0.7649 25.64 0.7225 30.44 0.7852 22.42 0.6949 27.64 0.7826 23.95 0.7699 realHAT-TG 27.76 0.7470 25.34 0.6933 30.53 0.7739 21.96 0.6622 26.93 0.7495 23.54 0.7426 本文模型 29.50 0.7857 27.27 0.7462 32.43 0.8068 23.45 0.7292 29.57 0.8060 25.39 0.7860