# Task-Driven Real-World Super-Resolution of Document Scans
## 4 Experimental Validation
### Experimental Results
& \(\mathbf{20.36\pm 6.03}\) & \(\mathbf{0.7043\pm 0.1890}\) & \(\mathbf{0.2973\pm 0.1893}\) & \(\mathbf{0.9038\pm 0.0993}\) & \(\mathbf{19.02\pm 6.32}\) & \(\mathbf{0.7403\pm 0.1994}\) & \(\mathbf{0.2516\pm 0.1863}\) & \(\mathbf{0.8820\pm 0.0961}\) \\ \(\mathcal{M}_{\Theta}\) & \(18.09\pm 5.35\) & \(0.6535\pm 0.1926\) & \(0.3222\pm 0.1914\) & \(0.9033\pm 0.0943\) & \(15.67\pm 5.39\) & \(0.6509\pm 0.2812\) & \(0.3073\pm 0.2074\) & \(0.8708\pm 0.0960\) \\ \(\mathcal{M}_{\Theta++}^{E}\) & \(15.52\pm 5.31\) & \(0.4512\pm 0.2423\) & \(0.4186\pm 0.1976\) & \(0.9119\pm 0.1029\) & \(13.72\pm 5.20\) & \(0.4182\pm 0.2698\) & \(0.4424\pm 0.2139\) & \(\mathbf{0.8984\pm 0.0979}\) \\ \(\mathcal{M}_{\Theta-+}^{E}\) & \(17.62\pm 3.98\) & \(0.6195\pm 0.1995\) & \(0.3083\pm 0.1541\) & \(0.9071\pm 0.1022\) & \(17.19\pm 4.38\) & \(0.6708\pm 0.1892\) & \(0.2799\pm 0.1471\) & \(0.8834\pm 0.1005\) \\ \(\mathcal{M}_{\Theta-+}^{E}\) & \(17.39\pm 3.86\) & \(0.6269\pm 0.2014\) & \(0.3032\pm 0.1608\) & \(0.9094\pm 0.0989\) & \(16.47\pm 4.04\) & \(0.6793\pm 0.1859\) & \(0.2723\pm 0.1544\) & \(0.8823\pm 0.1027\) \\ \(\mathcal{M}_{\Theta-}^{E}\) & \(14.93\pm 4.80\) & \(0.4990\pm 0.2206\) & \(0.4071\pm 0.1984\) & \(0.9040\pm 0.1191\) & \(13.97\pm 5.14\) & \(0.4091\pm 0.2579\) & \(0.4116\pm 0.2206\) & \(0.8635\pm 0.1233\) \\ \(\mathcal{M}_{  
==ERROR: No output for this page== \begin{table} \
\begin{tabular}{c c c c c c c c c c c c c c c c c c c c c} \hline \hline  & Int. & \(\mathbf{\mathcal{M}_{\rm B}}\) & \(\mathbf{\mathcal{M}_{\rm++}^{B}}\) & \(\mathbf{\mathcal{M}_{\rm++}^{B}}\) & \(\mathbf{\mathcal{M}_{\rm+}^{B}}\) & \(\mathbf{\mathcal{M}_{\rm+}^{B}}\) & \(\mathbf{\mathcal{M}_{\rm+}^{B}}\) & \(\mathbf{\mathcal{M}_{\rm++}^{B}}\) & \(\mathbf{\mathcal{M}_{\rm++}^{B}}\) & \(\mathbf{\mathcal{M}_{\rm++}^{B}}\) & \(\mathbf{\mathcal{M}_{\rm++}^{S}}\) & \\end{tabular}\end{table} 
+++  
}^{R}\) and \(\mathcal{M}_{-++}^{R}\) variants, each of which is significantly better than the 15 other variants, including bicubically-interpolated images and those obtained with the baseline \(\mathcal{M}_{\text{B}}\) variant (Table 11). Here, the models trained from the simulated data were also rather poor in terms of the IoU scores, which confirms the necessity of elaborating real-world training datasets for training SR networks. The statistical analysis reported for the IoU scores in Tables 7 and 11 also sheds light on the necessity of employing task-driven components of the loss function. For the simulated test set (Table 7), the \(\mathcal{L}_{\text{Key,Net}}\) and \(\mathcal{L}_{\text{Hue}}\) components are crucial (in addition to those based on the CTPN features). For the real-world test set, the best average score was obtained with all components switched on (\(\mathcal{M}_{+++}^{R}\)); however, the use of \(\mathcal{L}_{\text{CRNN}}\) does not improve the scores in a statistically significant way. Clearly, incorporating a loss function component related to text recognition does not enhance text detection capabilities, quantified with the IoU metric; however, it may be relevant in our future work, which will be aimed at incorporating text recognition to evaluate the SR outcome. It must also be noted that the improvements in IoU scores, although statistically significant, are limited due to the inherent constraints of running reconstruction from just a single image. While SISR techniques allow for substantial enhancement of perceived image quality, they contribute little to recovering genuine HR information. In contrast, multi-image SR benefits fromthe fact that every LR observation contains a different portion of HR information--as a result, reconstructed images are much closer to the actual ground truth than any of the LR inputs [4]. Importantly, the elaborated framework is not restricted to SISR, and it can be employed for training multi-image SR techniques. They may be expected to achieve considerably larger gains in terms of the OCR performance, benefiting from the task-driven guidance proposed in the study reported here.