## 3 Dark Current Noise Correction Experiment for the LWIR QWIP System
### Dark Current Noise Correction Experiment
Noise values before and after correction of the target imaging pixels were calculated using Equations (9) and (10), as shown in Table 2; after correction, noise was reduced by 49.17% on average. As a comparison, a conventional dark currents noise correction method is introduced: the response value in the imaging is subtracted from the mean response of dark pixels. The method is shown in Equation (11):  
\[g^{{}^{\prime}}_{\text{pixel\_method2}}(i,j,k)=g_{\text{pixel}}(i,j,k)-\frac{ \sum_{j=0}^{m1}\sum_{i=0}^{n1}g_{\text{dark}}(i,j,k)}{m_{1}\cdot n_{1}} \tag{11}\]  
where \(g^{{}^{\prime}}_{\text{pixel\_method2}}\) is the data corrected by this method. The correction effect was verified using Equations (9) and (10) for the same imaging pixels. Their noise was reduced by 37.30% on average. It is obvious that the method mainly described in the article works better. In the next experiment, four sets of target data at different target temperatures were collected and used to verify the calibration effect at different target temperatures. The calibration effect is shown in Table 3. The average correction effect for the four different sets of target temperature data was 49.02%. Therefore, the method is oriented to targets of different temperatures and the correction is stable. There was residual noise in the corrected imaging pixels, including photon noise from the target and the background, sampling noise from the information acquisition circuit, and readout circuit noise. There were also errors, including the RNN's prediction error and crosstalk between imaging pixels and dark pixels. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{2}{c}{**Pixel Coordinates/(\(i,j\))**} & \multicolumn{2}{c}{**Temporal Noise**} & \multicolumn{2}{c}{**Temporal Noise After**} & \multicolumn{1}{c}{**Noise Reduction Ratio**} \\ \multicolumn{2}{c}{} & **Before Correction** & \multicolumn{2}{c}{**Correction**} & \multicolumn{1}{c}{**Correction**} & \multicolumn{1}{c}{**Noise Reduction Ratio**} \\ \hline \multirow{4}{*}{Center} & (159, 112) & 4.05 & 2.02 & 50.37\% \\  & (151, 120) & 3.94 & 2.01 & 48.98\% \\  & (157, 139) & 3.92 & 2.05 & 47.70\% \\  & (160, 128) & 4.21 & 2.10 & 50.11\% \\ \hline \multirow{4}{*}{Edge} & (3, 71) & 4.13 & 2.11 & 48.91\% \\  & (158, 2) & 3.98 & 2.03 & 48.99\% \\  & (320, 202) & 4.32 & 2.12 & 50.93\% \\  & (162, 221) & 4.01 & 2.03 & 49.38\% \\ \hline \multirow{4}{*}{Other} & (186, 53) & 4.42 & 2.17 & 50.90\% \\  & (51, 125) & 3.96 & 2.01 & 49.24\% \\  & (261, 67) & 3.83 & 2.10 & 45.17\% \\ \cline{1-1}  & (190, 124) & 4.18 & 2.02 & 51.67\% \\ \cline{1-1}  & (255, 176) & 4.08 & 2.11 & 48.28\% \\ \cline{1-1}  & (82, 190) & 4.08 & 2.04 & 50.00\% \\ \cline{1-1}  & (134, 150) & 4.19 & 2.17 & 48.21\% \\ \cline{1-1}  & (221, 87) & 4.60 & 2.40 & 47.83\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Correction effect of imaged pixels. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Temperature of** & 296 & 298 & 300 & 305 \\
**the Target/k** & & & & \\ \hline
**Noise Reduction Ratio** & 48.82\% & 49.17\% & 49.30\% & 48.79\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Calibration effect at different target temperatures.