In space exploration optical imaging is one of the key measurements conducted, with a vast majority of missions heavily relying on optical data acquisition to examine alien worlds. One such endeavor is ESA’s F-class mission Comet Interceptor, a multi-element spacecraft expected to be launched in 2028. It consists of a primary platform and two sub-spacecraft, one of which carrying the Optical Periscopic Imager for Comets (OPIC). An accurate prediction of the generated imagery is of undeniable importance as mission planning and instrument design strongly depend on the real-world output quality of the camera system. In the case of OPIC, the collected image data will be used to reconstruct three dimensional models of targeted celestial bodies. Furthermore, the sub-spacecraft faces a risk of high velocity dust impacts, leading to a limited number of data samples to be broadcasted back to the primary spacecraft before collision. Testing image prioritization algorithms and reconstruction methods prior to mission start requires accurate computer-generated images. Camera sensors and lens systems are subjected to various optical distortions and aberrations that degrade the final image. Popular render engines model those effects to a certain degree only and as a result produce content that is looking too perfect. While more sophisticated software products exist, they often come with compatibility limitations and other drawbacks. This report discusses the most important optical aberrations, as well as their relevance for optical instruments in space applications with a particular focus on the Comet Interceptor mission. The main part of this work is however the implementation of a dedicated software tool that simulates a variety of optical aberrations complementing the basic camera model of the Blender render engine. While its functionality is mostly demonstrated for OPIC, the software is designed with a broad range of usage scenarios in mind.

Image processing algorithms have developed rapidly in recent years. Imaging functions are becoming more common in electronic devices, demanding better image quality, and more robust image capture in challenging conditions. Increasingly more complicated algorithms are being developed in order to achieve better signal to noise characteristics, more accurate colours, and wider dynamic range, in order to approach the human visual system performance levels.

The master´s thesis describes the basic information on the reporting of water losses. Means and methods to reduce water losses. Devices used to monitoring water supply, or detect malfunctioning of water supply line. Describes and evaluates the functionality of UFR on the laboratory model.