## 2 Related Work  
The problem of ME in general and for UAVs has been a topic of significant interest in recent years. A key focus has been on improving the efficiency and accuracy of block-matching ME algorithms. The researchers of [4] proposed an All-Direction Search (ADS) pattern, which searches for the best block in all possible directions. For further improvement in search speed, a halfway stop technique was applied in the search process. The results showed that the proposed ADS algorithm outperformed other state-of-the-art and eminent ME algorithms. This work is particularly relevant as it presents a novel approach to block-matching that can potentially enhance the performance of the DS algorithm. [PERSON] and [PERSON] [5] proposed an improved fast ME algorithm for H.266/VVC, where they replaced the DS model with an HS model. They also increased the number of initial matching search points of the rotation HS model, which led to a significant reduction in the overall coding time. [PERSON] and [PERSON] [6] studied the effects of a meta-heuristic algorithm on ME. They proposed the Firefly algorithm for ME, which saved a considerable amount of time with a comparable encoding efficiency. Multiple other ME optimizations have also been successfully implemented in [7; 8; 9; 10]. In the realm of user interaction, [PERSON] et al. [11] presented EyeRobot, a concept that enables dynamic viewpoints for telepresence using the intuitive control of the user's head motion. This approach could potentially be adapted for the MDIS ME algorithm. [PERSON] et al. [12] proposed a hybrid hand-gesture system that combines an inertial measurement unit (IMU)-based motion capture system and a vision-based gesture system to increase real-time performance. Their approach divided IMU-based commands and vision-based commands according to whether drone operation commands are continuously input. The work by [PERSON] et al. [13] on the validation of a Limit Ellipisis Controller (LEC) for rescue drones presents an innovative control algorithm designed for UAVs in emergency situations. In their study, the LEC was adapted for indoor environments, showcasing its potential to improve drone stability and maneuverability in semi-structured settings. The integration of our algorithm could further improve their system by optimizing the ME in both the visual and thermal camera equipped on the UAV. Similarly, [14] illustrates the significant utility of drones in outdoor safety and rescue operations, particularly in expediting the search for missing persons. The real-time video feed provided by UAVs is essential for drone pilots to make timely and informed decisions. In these scenarios, it is critical that the video feed is both promptly available and of high quality. Our algorithm aligns well with these requirements by enhancing the overall encoding speed, thereby ensuring quicker end-to-end video transmission. Generally, our algorithm could be implemented to improve ME in various domains, like construction, agriculture, or mining [15; 16; 17; 18]. Classical forms of user interaction, such as joysticks, have been fundamental in RCV control, providing direct manipulation of the vehicle's movement. Modern systems continue to use these traditional controls while integrating advanced features like vibration feedback and ergonomic design to enhance user experience and control accuracy [19]. These systems are often complemented by templates or predefined paths that can guide the drone's motion, as seen in traditional remote-controlled aircraft systems. Semi-autonomous systems, where a human operator sets high-level goals or waypoints for the drone to follow, also play a crucial role. For example, recent advancements have shown the integration of intuitive control systems like handheld controllers with high-resolution displays and robust wireless communication, significantly enhancing operational efficiency and user interaction. Systems like those described by [PERSON] et al. [20] and [PERSON] et al.