## 5 Conclusions  
This work presents a framework of improving underexposed images using image enhancement algorithms for feature identification with implementation in close-range photogrammetry and structural health monitoring. An experimental validation with systematic evaluation was conducted using a one-inch steel block text which measured the absolute difference between two vision-based systems and the one-inch block displacement. The framework was also tested in measuring the seismic response and modal properties of a three-story building tested under high-amplitude seismic excitation and a white noise test. Based on these laboratory experiments, the key findings and main conclusions can be drawn as follows:  
* Image enhancement efficiently improves the quality of image data collected from vision-based sensors and needs to be adopted more often in infrastructure and large-scale SHM applications. The proposed algorithms can modify the underexposed and low-contrast input images captured by high-speed or commercial DSLR cameras, thus allowing automatic feature identification. Their efficiency can be estimated through the classical image quality metrics, and their output quality can be assessed by more advanced blind image quality metrics. * The precision of the enhanced images in measuring static displacement shows a very high accuracy as observed by the two vision systems in the one-inch block test. Comparable results from both systems were also assessed in measuring high-amplitude displacement from the large-scale seismic tests, and in estimating structural modal properties through the system identification procedure. * Overall, it is concluded that image enhancement does have a significant effect on feature identification and implications for the close-range photogrammetry and SHM accuracy. The applied enhancement algorithms were shown to be computationally effective and are recommended for vision-based SHM image enhancement applications. * On a specific note, automatic feature detection in enhanced images may be a limitation of this method. Thus, future users are cautioned against selecting the search window and the threshold options for enabling automatic detection of the features on the output images when the global enhancement algorithms are implemented. Instead, a careful check is recommended of the number of obsolete objects identified \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & & & & \multicolumn{4}{c}{**Transverse Mode**} & & \\ \hline System & \(f_{1}\) (Hz) & System & \(f_{1}\) (Hz) & \(\Delta_{f}\) (\%) & System & \(\zeta_{1}\) (\%) & System & \(\zeta_{1}\) (\%) & \(\Delta_{\zeta}\) (\%) \\ HS & 6.47 & SD & 6.44 & 0.46 & HS & 4.65 & SD & 4.51 & 3.01 \\ \hline \hline \multicolumn{10}{c}{**Longitudinal Mode**} & & & & & \\ \hline System & \(f_{1}\) (Hz) & System & \(f_{1}\) (Hz) & \(\Delta_{f}\) (\%) & System & \(\zeta_{1}\) (\%) & System & \(\zeta_{1}\) (\%) & \(\Delta_{\zeta}\) (\%) \\ HS & 6.12 & SD & 5.91 & 3.43 & HS & 2.53 & SD & 2.61 & 3.16 \\ \hline \hline \multicolumn{10}{c}{**Vertical Mode**} & & & & & \\ \hline System & \(f_{1}\) (Hz) & System & \(f_{1}\) (Hz) & \(\Delta_{f}\) (\%) & System & \(\zeta_{1}\) (\%) & System & \(\zeta_{1}\) (\%) & \(\Delta_{\zeta}\) (\%) \\ HS & 8.59 & SD & 8.84 & 2.91 & HS & 2.70 & SD & 2.62 & 2.96 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Building fundamental frequency \(f_{1}\), and damping, \(\zeta_{1}\), with their differences, \(\Delta_{f}\) and \(\Delta_{\zeta}\), as measured by two-vision systems. within each enhanced image plane to allow the bundle adjustment to converge in the photogrammetry process. Measurement accuracy seems to slightly deteriorate when more failed images are identified from the bundle adjustment procedures. With due care, successful monitoring using underexposed and low-contrast images is still possible, not only for different vision system hardware, but also for a wide range of experimental works, through a proper selection of the image enhancement algorithm. Conceptualization, L.N. and M.A.M.