# On-Board Flickering Pixel Dynamic Suppression Method Based on Multi-Feature Fusion
## 3 Experimental Results and Discussion
### Results and Discussion
Figure 7: The blind pixel maps of the first sequence of each scenario detected by different methods (**a**) Background: sky Method: the proposed method; (**b**) Background: sky Method: SBBPDC; (**c**) Background: sky Method: CBATBPD; (**d**) Background: sky with IRPT Method: the proposed method; (**e**) Background: sky with IRPT Method: SBBPDC; (**f**) Background: sky with IRPT Method: CBATBPD; (**g**) Background: deep space Method: the proposed method; (**h**) Background: deep space Method: SBBPDC; (**i**) Background: deep space with IRPT Method: the proposed method; (**j**) Background: deep space with IRPT Method: SBBPDC. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Blind Pixel Detection Method**} & \multicolumn{8}{c}{**Application Scenarios**} \\ \cline{2-13}  & \multicolumn{3}{c}{**Cloud**} & \multicolumn{3}{c}{**Cloud with Target**} & \multicolumn{3}{c}{**Deep Space**} & \multicolumn{3}{c}{**Deep Space with Target**} \\ \cline{2-13}  & \(N_{bp}\) & \(R_{bp}\) **(\%)** & \(T_{pf}\) **(s)** & \(N_{bp}\) & \(R_{bp}\) **(\%)** & \(T_{pf}\) **(s)** & \(N_{bp}\) & \(R_{bp}\) **(\%)** & \(T_{pf}\) **(s)** & \(N_{bp}\) & \(R_{bp}\) **(\%)** & \(T_{pf}\) **(s)** \\ \hline SBBPDC & 62 & 1.61 & 0.71 & 69 & 1.45 & 0.99 & 37 & 0 & 0.71 & 32 & 0 & 0.89 \\ CBATBPD & 37 & 10.8 & 1.17 & 34 & 8.82 & 1.02 & — & — & — & — & — & — \\
**Proposed** & **98** & **1.02** & **0.36** & **100** & **1.00** & **0.46** & **40** & **0** & **0.34** & **38** & **0** & **0.34** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The situation of blind pixels detected in four application scenarios. In order to discuss the time consumption of our proposed method in practical applications, we recorded the average frame time consumption of each step in different scenarios in Table 4. The average frame time consumption of blind pixels detection and compensation is about 0.09 s. After code optimization and parallel acceleration, the time-consuming situation of our method can be further improved. Furthermore, in practical applications, our method can work once every two to three frames to ensure the near-real-time suppression of blind pixels. Moreover, it is important to note, owing to the limitation of the transmission bandwidth and computing resource, the current frame rate of IRPT detection and tracking application usually only reaches 5-20 frames per second. In the terms of flickering pixel suppression, our proposed method is to achieve frame-accurate dynamical flickering pixel suppression. For instance, the pixel (347,487) was detected as a flickering pixel in the second sequence of cloud scenario and Figure 9 shows the suppression situation of this pixel. The CFP of this pixel was less than Th\({}_{\text{V}}\) before the 18 th frame, so this pixel was not suppressed. After the 18 th frame, our method accurately suppresses this pixel when the response is too low. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Time Consumption** & **Cloud** & **Cloud with Target** & **Deep Space** & **Deep Space with Target** \\ \hline IRPT detection & & & & \\ (Median filter and threshold segmentation) & 0.111 s & 0.121 s & 0.109 s & 0.112 s \\ \hline IRPT tracking & & & & \\ (Interframe matching) & 0.156 s & 0.247 s & 0.135 s & 0.141 s \\ \hline Blind pixels detection & & & & \\ and compensation & 0.091 s & 0.089 s & 0.091 s & 0.090 s \\ \hline Total & 0.358 s & 0.457 s & 0.335 s & 0.343 s \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The average frame time consumption of each step of our method used in the above experiment in different scenarios. Figure 8: The number of blind pixels detected by different methods in each frame (**a**) sky background; (**b**) sky background with IRPT; (**c**) deep space background; (**d**) deep space background with IRPT. Meanwhile, we use the simulated data to make a quantitative analysis on the flickering pixel suppression. Figure 10 shows the randomly added flickering pixels and miss-suppressed flickering pixels of our method.