# Image Error Concealment Based on Deep Neural Network
## 4 Experiments
### Objective and Subjective Performance Comparison
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Images**} & \multirow{2}{*}{**Metrics**} & \multicolumn{8}{c}{**Methods**} \\ \cline{3-10}  & & **POCS** & **OAI** & **AVC** & **CAD** & **MRF** & **VC** & **SLP** & **KMMSE** & **Ours** \\ \hline \multirow{3}{*}{**Baboon**} & PSNR & 21.38 & 22.77 & 22.27 & 19.81 & 22.94 & 21.76 & 21.26 & 22.92 & **22.95** \\  & SSIM & 0.6719 & 0.7305 & 0.6981 & 0.6554 & 0.7202 & 0.6872 & 0.7013 & **0.7228** & 0.7208 \\ \hline \multirow{3}{*}{**Barbara**} & PSNR & 21.32 & 25.19 & 23.36 & 22.16 & 24.23 & 22.65 & 25.36 & **26.59** & 26.53 \\  & SSIM & 0.6993 & 0.8407 & 0.7693 & 0.772 & 0.8019 & 0.7531 & 0.8520 & **0.8620** & 0.8593 \\ \hline \multirow{3}{*}{**Boat**} & PSNR & 23.89 & 24.14 & 24.83 & 22.59 & 24.80 & 23.32 & 23.46 & 24.53 & **24.93** \\  & SSIM & 0.7427 & 0.7942 & 0.7892 & 0.7613 & 0.7781 & 0.7376 & 0.7716 & 0.7833 & **0.7951** \\ \hline \multirow{3}{*}{**Butterfly**} & PSNR & 18.11 & 21.11 & 18.91 & 19.42 & 20.61 & 19.97 & 20.24 & 21.10 & **22.77** \\  & SSIM & 0.7062 & 0.8429 & 0.7556 & 0.7925 & 0.8260 & 0.7809 & 0.8623 & 0.8693 & **0.8814** \\ \hline \multirow{3}{*}{**Columbia**} & PSNR & 21.66 & 24.17 & 22.91 & 23.74 & 23.48 & 24.12 & 23.35 & 24.23 & **25.05** \\  & SSIM & 0.7722 & **0.8679** & 0.8454 & 0.8537 & 0.8280 & 0.8172 & 0.8600 & 0.8665 & 0.8655 \\ \hline \multirow{3}{*}{**Cornfield**} & PSNR & 23.84 & 24.88 & 25.31 & 23.07 & 25.12 & 24.35 & 24.13 & 25.27 & **25.66** \\  & SSIM & 0.7927 & 0.8624 & 0.8563 & 0.8172 & 0.8393 & 0.7859 & 0.8492 & 0.8617 & **0.8651** \\ \hline \multirow{3}{*}{**Couple**} & PSNR & 21.95 & 24.62 & 23.96 & 22.17 & 23.55 & 22.94 & 22.56 & 23.54 & **24.76** \\  & SSIM & 0.7191 & 0.8118 & 0.782 & 0.773 & 0.7747 & 0.7510 & 0.7748 & 0.7886 & **0.7940** \\ \hline \multirow{3}{*}{**Goldhill**} & PSNR & 23.61 & 25.37 & 25.44 & 23.50 & 25.24 & 24.69 & 24.75 & 25.43 & **25.62** \\  & SSIM & 0.7321 & 0.7995 & 0.7818 & 0.7489 & 0.7785 & 0.7594 & 0.7822 & 0.7908 & **0.7920** \\ \hline \multirow{3}{*}{**Hat**} & PSNR & 24.52 & 28.40 & 26.27 & 24.18 & 27.57 & 25.17 & 27.31 & 27.73 & **28.62** \\  & SSIM & 0.7947 & 0.8913 & 0.8606 & 0.8128 & 0.8844 & 0.7931 & 0.8954 & 0.8998 & **0.9010** \\ \hline \multirow{3}{*}{**Man**} & PSNR & 19.77 & 22.14 & 21.77 & 17.17 & 22.13 & 21.60 & 21.02 & 22.06 & **22.49** \\  & SSIM & 0.6668 & 0.7501 & 0.72 & 0.6701 & 0.7390 & 0.7085 & 0.7310 & 0.7461 & **0.7542** \\ \hline \multirow{3}{*}{**Peperpers**} & PSNR & 20.88 & 25.73 & 23.16 & 19.71 & 24.14 & 23.18 & 23.52 & 24.14 & **25.76** \\  & SSIM & 0.7209 & 0.8516 & 0.8055 & 0.7696 & 0.8319 & 0.7770 & 0.8371 & 0.8434 & **0.8530** \\ \hline \multirow{3}{*}{**Cameraman**} & PSNR & 20.42 & **24.06** & 22.41 & 20.42 & 22.62 & 22.51 & 22.63 & 23.16 & 23.74 \\  & SSIM & 0.7654 & 0.8704 & 0.8417 & 0.8333 & 0.8475 & 0.7941 & 0.8753 & **0.8757** & 0.8747 \\ \hline \multirow{3}{*}{**Tower**} & PSNR & 20.37 & 23.47 & 22.78 & 21.04 & 22.25 & 22.47 & 23.35 & **23.96** \\  & SSIM & 0.7499 & 0.8339 & 0.8106 & 0.7826 & 0.8030 & 0.7704 & 0.8311 & **0.8407** & 0.8554 \\ \hline \multirow{3}{*}{**Average**} & PSNR & 21.67 & **24.31** & 23.34 & 21.46 & 23.73 & 22.99 & 23.24 & 24.16 & **24.83** \\  & SSIM & 0.7334 & 0.8267 & 0.7935 & 0.7725 & 0.8040 & 0.7627 & 0.8172 & 0.8270 & **0.8301** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: PSNR and SSIM comparison of EC algorithms with \(16\times 16\) regular consecutive block losses. Figure 19: Subjective comparison of different EC algorithms on the Barbara image with \(16\times 16\) isolate block loss. The corresponding PSNR and SSIM values are also shown in the upper left corner.