双维度交叉融合驱动的图像超分辨率重建方法

贾晓芬,王子祥,赵佰亭,梁镇洹,胡锐

Image super-resolution reconstruction method driven by two-dimensional cross-fusion

Xiaofen JIA,Zixiang WANG,Baiting ZHAO,Zhenhuan LIANG,Rui HU

表 4 所提方法在5个基准数据集上与先进方法的对比

Tab.4 Comparison with advanced methods on five benchmark datasets

方法 年份 倍数 Set5 Set14 BSD100 Urban100 Manga109 PSNR/dB SSIM PSNR/dB SSIM PSNR/dB SSIM PSNR/dB SSIM PSNR/dB SSIM IMDN[17] 2019 ×2 38.00 0.9605 33.63 0.9177 32.19 0.8996 32.17 0.9283 — — HAN[19] 2019 ×2 38.27 0.9614 34.16 0.9217 32.41 0.9027 33.35 0.9385 39.46 0.9785 SAN[32] 2020 ×2 38.31 0.9620 34.07 0.9213 32.42 0.9028 33.10 0.9370 39.32 0.9792 RFANET[33] 2020 ×2 38.26 0.9615 34.16 0.9220 32.41 0.9026 33.33 0.9389 39.44 0.9783 NLSN[34] 2021 ×2 38.34 0.9618 34.08 0.9231 32.43 0.9027 33.42 0.9394 39.59 0.9789 EMT[35] 2024 ×2 38.29 0.9615 34.23 0.9229 32.40 0.9027 33.28 0.9385 39.59 0.9789 BiGLFE[36] 2024 ×2 38.15 0.9601 33.80 0.9194 32.29 0.8994 32.71 0.9329 38.96 0.9771 CMSN[37] 2024 ×2 38.18 0.9612 33.84 0.9195 32.30 0.9014 32.65 0.9329 39.11 0.9780 CGT(本研究模型) 2024 ×2 38.36 0.9618 34.11 0.9220 32.41 0.9026 33.48 0.9395 39.67 0.9792 IMDN[17] 2019 ×3 34.36 0.9270 30.32 0.8417 29.09 0.8046 28.17 0.8519 33.61 0.9445 HAN[19] 2019 ×3 34.75 0.9299 30.67 0.8483 29.32 0.8110 29.10 0.8705 34.48 0.9500 SAN[32] 2020 ×3 34.75 0.9300 30.59 0.8476 29.33 0.8112 28.93 0.8671 34.30 0.9494 RFANET[33] 2020 ×3 34.79 0.9300 30.67 0.8487 29.34 0.8115 29.15 0.8720 34.59 0.9506 NLSN[34] 2021 ×3 34.85 0.9306 30.70 0.8485 29.34 0.8117 29.25 0.8726 34.57 0.9508 EMT[35] 2024 ×3 34.80 0.9303 30.71 0.8489 29.33 0.8113 29.16 0.8716 34.65 0.9508 BiGLFE[36] 2024 ×3 34.59 0.9276 30.33 0.8449 29.24 0.8059 28.76 0.8642 34.03 0.9460 CMSN[37] 2024 ×3 34.62 0.9288 30.50 0.8452 29.22 0.8082 28.60 0.8612 34.12 0.9476 CGT(本研究模型) 2024 ×3 34.91 0.9308 30.75 0.8496 29.36 0.8119 29.26 0.8729 34.77 0.9514 IMDN[17] 2019 ×4 32.21 0.8948 28.58 0.7811 27.56 0.7353 26.04 0.7838 — — HAN[19] 2019 ×4 32.59 0.9000 28.87 0.7891 27.78 0.7444 26.96 0.8109 31.27 0.9184 SAN[32] 2020 ×4 32.64 0.9003 28.92 0.7888 27.78 0.7436 26.79 0.8068 31.18 0.9169 RFANET[33] 2020 ×4 32.66 0.9004 28.88 0.7894 27.79 0.7442 26.92 0.8112 31.41 0.9187 NLSN[34] 2021 ×4 32.64 0.9002 28.90 0.7890 27.80 0.7442 26.85 0.8094 31.42 0.9177 EMT[35] 2024 ×4 32.64 0.9003 28.97 0.7901 27.81 0.7441 26.98 0.8118 31.48 0.9190 BiGLFE[36] 2024 ×4 32.52 0.8971 28.64 0.7858 27.74 0.7377 26.60 0.8016 31.00 0.9123 CMSN[37] 2024 ×4 32.41 0.8975 28.77 0.7851 27.68 0.7398 26.44 0.7964 31.00 0.9133 CGT(本研究模型) 2024 ×4 32.81 0.9024 29.03 0.7921 27.85 0.7456 27.12 0.8155 31.81 0.9224