Space debris represents a growing threat for both current spacecraft and future launches. This is exceptionally alarming in the case of low Earth orbits, where chain impacts of existing debris generate even more fragments, increasing the probability of further collisions. The now defunct satellite Envisat represents one of the largest objects classified as space debris. The e.Deorbit mission will demonstrate active debris removal (ADR) technology to successfully decommission Envisat and other non-functional target spacecraft in orbit. Relative navigation solutions shall be achieved using image processing algorithms, which implies the detection and matching of two-dimensional regions of interest. In this work, multiple pattern recognition techniques are investigated for the detection and description of these features. This analysis of feature perception is achieved for the first time in the context of space non-cooperative rendezvous (NCRV) across two different modalities: the visible (0.39-0.70 μm) and the thermal infrared (8-14 μm). The assessed algorithms are implemented in a dedicated, space-appropriate hardware processor to benchmark their real-time capabilities.