## 1 Introduction
#### Current Advances in Related Research  
Unmanned aerial vehicles (UAVs) are a transformative technology showing tremendous promise for several sectors, one of which is the maritime industry. A closer analysis reveals a range of perks offered by these vehicles: the efficient retrieval of data streams and advanced surveillance standards, preserving public safety while substantially cutting costs for operators. Nevertheless, many impediments need to be overcome before this budding technology can be fully deployed in mission-critical tasks involving vessels: regulations on multiple levels, limited technical capacities, and adverse operating circumstances all pose formidable challenges. In order to achieve the maximum potential in marine-based application scenarios, it is essential that related issues are addressed comprehensively. Over the course of several consecutive years, numerous research teams have dedicated their efforts to overcome various challenges associated with operating UAVs in maritime conditions. The constraints imposed by limited resources such as specialists, work hours, and available deck space on ships and boats pose major challenges. Consequently, engineers have been compelled to develop autonomous systems that are both maintenance-free and reliable. Nevertheless, the creation of fully autonomous solutions that can be used in commercial applications has proved to be exceedingly expensive and financially unfeasible for many companies and research institutions. As a result, progress has been made incrementally within specific domains of expertise. One of the main applications of the UAV in maritime conditions is photogrammetry, which is a technique to create detailed and accurate 3D maps using aerial photography. The development and evolution of the UAV in terms of operational costs and reliability have substantially increased the accessibility and efficiency of photogrammetry [8]. This is even more important at sea due to the increased costs and risks of manned flights. UAVs are easy to deploy and offer a reasonably high spatial resolution and accuracy. The determination of high-density models of the sea floor utilizing LIDAR data acquired by a UAV was presented in [9]. The data resolution is a vital parameter in various aerial imaging tasks. When faced with limitations due to the small size and weight of the measuring devices, artificial-intelligence-based enhancement techniques can be employed to overcome these limitations. In a research study presented in [10], the set of super-resolution (SR) methods was explored, including those that leverage the concept of generative adversarial networks (GANs). These techniques aim to enhance the acquired information and improve the resolution of aerial imagery, enabling more detailed and accurate analysis. By leveraging advanced algorithms and deep learning approaches, SR methods offer potential solutions to enhance the quality and level of detail in aerial images, thereby expanding their applicability in different domains. Search and rescue (SAR) missions are another prominent field where UAVs have been widely utilized. Specifically, vertical take-off and landing (VTOL) platforms are commonly employed for conducting extensive marine surveillance with a focus on wide-area coverage and continuous monitoring. Numerous systems have been specifically designed for this purpose, as highlighted in [11; 12]. Additionally, the development of various UAV systems has taken into consideration the requirements and challenges associated with SAR missions, as referenced in [13]. This underscores the significance of UAV technology in enhancing search and rescue operations, particularly in maritime environments. The overall performance of a UAV in various tasks is not only dependent on advancements in data acquisition and processing for specific applications but also relies heavily on the UAV's parameters and its ability to comply with system commands.