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• Phisically-based thermal infrared images rendering chain for artificial satellite targets. • Assessment and comparison of most relevant pixel-level VIS-TIR image fusion techniques. • Fused noisy image processing within the context of uncooperative space-craft relative navigation. State-of-the-art techniques for vision-based relative navigation rely on images acquired in the visible spectral band. Consequently, the accuracy and robustness of the navigation is strongly influenced by the illumination conditions. The exploitation of thermal-infrared images for navigation purposes is studied in the present paper, as a possible solution to improve navigation in close proximity with a target spacecraft. Thermal-infrared images depend on the thermal radiation emitted by the target, hence, they are independent from light conditions; however, they suffer from a poorer texture and a lower contrast with respect to visible ones. This paper proposes pixel-level image fusion to overcome the limitations of the two types of images. The two source images are merged into a more informative one, retaining the strengths of the distinguished sensing modalities. The contribution of this work is twofold: firstly, a realistic thermal infrared images rendering tool for artificial targets is implemented; secondly, different pixel-level visible-thermal infrared images fusion techniques are assessed through qualitative and quantitative performance metrics to ease and improve the subsequent image processing step. The work presents a comprehensive evaluation of the best fusion techniques for on-board implementation, paving the way to the development of a multispectral end-to-end navigation chain. [ABSTRACT FROM AUTHOR]

Recent studies demonstrate the possibility of navigating in proximity of uncooperative space resident objects by using only monocular images. Despite the results achieved, the development and testing of new algorithms are strongly constrained by the availability of spaceborne image datasets. To overcome this, a new algorithm embedded in a tool to generate synthetic high-fidelity spaceborne image datasets is presented here. The architecture developed can be tailored to a wide range of scenarios and it is based on an open-source ray-tracing software. All assumptions and simplifications adopted are discussed in detail for the different models considered, including a trade-off between accuracy and rendering time. The new method described is subsequently adapted to a baseline scenario where the optical properties of a reference spacecraft model are tuned. Both qualitative and quantitative validations are detailed and successfully carried out for the baseline case, demonstrating the high photo-realism achievable with the proposed method. As a consequence of this main outcome, the paper details the generation of labeled spaceborne image datasets publicly available and reports the analyses that confirm the high level of representativeness, making them suitable for training and testing image-based navigation algorithms. As another outcome, the most comprehensive multi-purpose labeled dataset of validated spaceborne synthetic images currently publicly available is presented. • New methodology to generate spaceborne synthetic images via open-source ray-tracer. • Detailed analysis of atmosphere and topology modeling for celestial bodies. • Definition of a qualitative and quantitative validation step via image comparison. • Successful validation of the proposed approach and generation of validated datasets. • Detail of the largest multi-purpose labeled spaceborne image dataset available. [ABSTRACT FROM AUTHOR]