# Spatial Domain-Based Nonlinear Residual Feature Extraction for Identification of Image Operations
## 3 Experiments and Discussions
### Detection and Classification of Various Image Postprocessing Operations
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c} \hline \hline
**Actual/Predicted** & **Orig** & **GC** & **HE** & **UM** & **Rot** & **Sca** & **MeanF** & **MedF** & **WF** & **GF** & **JPEG** & **JP2** & **LPF** & **HPF** & **HF** & **BF** \\ \hline Orig & **87.5** & 0.4 & * & * & * & * & * & * & * & * & * & * & * & 2.4 & * & 1.6 & * & * \\ \hline GC & 2 & **92.9** & 2.4 & 1.4 & 0.8 & * & * & 0.4 & * & * & 0.8 & 0.8 & * & * & * & * \\ \hline HE & * & 0.2 & **98.7** & 0.3 & * & * & * & 0.1 & 0.2 & * & * & * & * & * & * \\ \hline UM & 3.2 & 1.4 & 0.3 & **93.5** & * & * & * & 0.4 & 0.3 & * & * & 1 & * & * & * & * \\ \hline Rot & 1.5 & 1.4 & * & * & **92.2** & 0.5 & * & * & * & * & * & * & 2 & * & 2 & * \\ \hline Sca & 1.5 & * & * & 0.4 & * & **87.8** & * & * & * & * & * & * & 0.5 & 3 & * & 3 \\ \hline MeanF & 0.3 & * & * & * & * & * & * & 99.7 & * & * & * & * & * & 0 & * & * \\ \hline MedF & * & * & 0.8 & * & 0.4 & 0.4 & * & **97.1** & * & * & * & 0.2 & * & * & * & 0.2 \\ \hline WF & * & * & * & * & * & * & * & * & * & 99.6 & * & * & * & * & * & * \\ \hline GF & 1 & * & * & * & * & 0.4 & * & * & * & **94.8** & 2 & * & * & * & * \\ \hline JPEG & * & 0.4 & * & 0.4 & * & 0.4 & * & 0.4 & 0.4 & * & **88.5** & 0.8 & 0.5 & 0.2 & 2 & 1 \\ \hline JP2 & 1 & 0.4 & * & * & * & 0.4 & * & 0.4 & * & * & 2.4 & **89.7** & * & 0.2 & * & * \\ \hline LPF & 0.3 & * & * & * & * & * & * & * & * & * & * & * & 97.5 & * & * & * \\ \hline HPF & 0.2 & 0.1 & * & * & * & * & * & 0.1 & * & 0.2 & * & * & 0.1 & **98.2** & 0.1 & * \\ \hline HF & 0.5 & * & * & * & * & 1 & 0.5 & 0.7 & 2.5 & 0.3 & * & * & * & * & **82.2** & * \\ \hline BF & 1.1 & 0.8 & * & 1 & * & * & * & 0.5 & * & * & * & * & * & * & 1.6 & **81.1** \\ \hline \hline \end{tabular} Note: symbol * indicates that the predicted percentage is under 0.1%.  
\end{table} 
Table 4: Identification of various image postprocessing operations using the proposed SDNR features and AlexNet [28] (%). \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c} \hline \hline
**Actual/Predicted** & **Orig** & **GC** & **HE** & **UM** & **Rot** & **Sca** & **MeanF** & **MedF** & **WF** & **GF** & **JPEG** & **JP2** & **LPF** & **HPF** & **HF** & **BF** \\ \hline Orig & **94.6** & 0.4 & * & * & * & * & * & * & * & * & * & * & * & 2.4 & * & 1.6 & * & * \\ \hline GC & 2 & **93.7** & 2.4 & 1.4 & 0.8 & * & * & 0.4 & * & * & 0.8 & 0.8 & * & * & * & * \\ \hline HE & * & 0.2 & **99.1** & 0.3 & * & * & * & 0.1 & 0.2 & * & * & * & * & * & * \\ \hline UM & 3.2 & 1.4 & 0.3 & **93.2** & * & * & * & 0.4 & 0.3 & * & * & 1 & * & * & * & * \\ \hline Rot & 1.5 & 1.4 & * & * & **93.3** & 0.5 & * & * & * & * & * & * & 2 & * & 2 & * \\ \hline Sca & 1.5 & * & * & 0.4 & * & **92.8** & * & * & * & * & * & * & 0.5 & 3 & * & 3 \\ \hline MeanF & 0.3 & * & * & * & * & * & * & 99.7 & * & * & * & * & * & 0 & * & * \\ \hline MedF & * & * & 0.8 & * & 0.4 & 0.4 & * & 98 & * & * & * & 0.2 & * & * & * & 0.2 \\ \hline WF & * & * & * & * & * & * & * & * & 100 & * & * & * & * & * & * \\ \hline GF & 1 & * & * & * & * & 0.4 & * & * & * & 96.6 & 2 & * & * & * & * \\ \hline JPEG & * & 0.4 & * & 0.4 & * & 0.4 & * & 0.4 & * & **92.5** & 0.8 & 0.5 & 0.2 & 2 & 1 \\ \hline JP2 & 1 & 0.4 & * & * & * & 0.4 & * & 0.4 & * & * & 2.4 & **92.5** & * & 0.2 & * & * \\ \hline LPF & 0.3 & * & * & * & * & * & * & * & * & * & * & **92.7** & * & * & * \\ \hline HPF & 0.2 & 0.1 & * & * & * & * & 0.1 & * & 0.2 & * & * & 0.1 & **99.2** & 0.1 & * \\ \hline HF & 0.5 & * & * & * & * & 1 & 0.5 & 0.7 & 2.5 & 0.3 & * & * & * & * & 95.3 & * \\ \hline BF & 1.1 & 0.8 & * & 1 & * & * & * & 0.5 & * & * & * & * & * & * & 1.6 & 94.6 \\ \hline \hline \end{tabular} Note: symbol * indicates that the predicted percentage is under 0.1%.  
\end{table} 
Table 5: Identification of various image postprocessing operations using the proposed SDNR features and the employed CNN classifier (%).