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Table 7 SSIM and PSNR performance achieved by different depth enhancement methods on Middlebury dataset and RGBD dataset

From: Robust depth enhancement and optimization based on advanced multilateral filters

Methods Art Books Doily Moebius RGBD_1 RGBD_2
SSIM PSNR SSIM PSNR SSIM PSNR SSIM PSNR SSIM PSNR SSIM PSNR
JBF [16] + CHF 0.9880 36.0083 0.9754 33.8966 0.9913 44.6455 0.9912 39.7306 0.9561 29.8534 0.9686 33.6112
IGDS [39] + CHF 0.9911 37.4257 0.9913 37.2058 0.9951 47.7032 0.9887 38.1115 0.9610 29.9120 0.9677 33.5204
CSDU [40] + CHF 0.9895 37.2223 0.9902 37.1560 0.9947 47.8200 0.9881 37.0544 0.9612 30.4155 0.9691 33.8235
AJTF [18] + CHF 0.9865 35.1333 0.9744 34.1137 0.9967 47.8452 0.9876 36.4653 0.9582 30.2524 0.9674 33.2741
AMF 0.9945 38.9374 0.9940 40.4719 0.9962 47.7070 0.9956 40.5725 0.9633 31.1112 0.9741 34.6881
AMF + RCR 0.9946 38.9546 0.9935 37.3574 0.9976 49.6378 0.9979 42.2108 0.9664 31.2685 0.9756 34.7168