Experiments and Results --generalizability Method SROCC LCC Best Method SROCC LCC Best Method SROCC LCC Best FTW 30] 0.3290 0.3358 VsQM [31 0.2358 0.3324 FTW [30] 0.3352 0.2900 FTW [30] 0.3154 0.3313 PSNR 0.6894 0.6875 VsQM 31] 0.3236 0.2374 VsQM [31] 0.2259 0.3233 SSIM 0.8172 0.8544 PSNR 0.5152 0.5073 PSNR 0.6715 0.6587 MS-SSIM [13] 0.7986 0.8345 SSIM [1] 0.7015 0.7219 SSIM [1] 0.8177 0.8408 SSIMplus [49] 0.8025 0.8414 MS-SSIM [13] 0.6800 0.7104 MS-SSIM [13] 0.7928 0.8168 PSNR+SQI [321 0.7800 0.7535 SSIM+SQI 32] 0.9085 0.9028 PSNR+SQI 321 0.5904 0.5905 PSNR+SQI [32 0.7492 0.7316 MS-SSIM+SQI [32] 0.8891 0.8808 SSIM+SQI [32] 0.7451 0.7070 SSIM+SQI [32] 0.9009 0.8897 SSIMplus+SQI [32] 0.9103 0.9012 MS-SSIM+SQI 32] 0.7239 0.6848 MS-SSIM+SQI [32 0.8807 0.8652 PSNR+ATLAS 0.7799 0.7510 SVR PSNR+ATLAS 0.6155 0.6116 SVR PSNR+ATLAS 0.7439 0.7254 SVR SSIM+ATLAS 0.9142 0.9097 SVR SSIM+ATLAS 0.8203 0.7813 Lasso SSIM+ATLAS 0.9090 0.8963 Lasso MS-SSIM+ATLAS 0.8955 0.8880 Lasso SSIMplus+ATLAS 0.9084 0.8981 Ridge MS-SSIM+ATLAS 0.8000 0.7670 Lasso MS-SSIM+ATLAS 0.8888 0.8716 Lasso Training and Testing for Waterloo training on Waterloo and testing on LIVE-Netflflix training on LIVE-Netflflix and testing on WaterlooExperiments and Results -- generalizability Training and Testing for Waterloo training on Waterloo and testing on LIVE-Netflflix training on LIVE-Netflflix and testing on Waterloo