<p>On-board image processing represents a practical application for satellite imagery, aiming to optimize or prioritize data transmission to ground stations, thereby enhancing bandwidth utilization. In addition to their low cost and reduced development time, nanosatellites have experienced significant growth in applications and capabilities as technology advances. Presently, the implementation of on-board image processing has been successfully tested on real nanosatellite missions. Earth observation stands as the most utilized application for nanosatellites equipped with on-board imagers, and integrating image processing in those nanosatellites would enhance the overall performance of the mission. Hence, this article is a systematic review that investigates the current advancements and trends in terms of applications and technologies in the context of image processing on-board nanosatellites. To conduct the study systematically, Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were utilized. After the search and screening process, 73 relevant publications were analyzed to extract pertinent data for the review. The findings outlined a particular interest toward the application of deep learning methods on-board nanosatellites, especially for applications such as image classification or image segmentation.</p>