Identifying resident space objects (RSOs) in arbitrary space imagery with little a-priori information is a challenging, yet crucial next step in space-domain awareness applications. This work proposes improvements to an existing RSO identification process for unresolved space images. The algorithm has three main phases: image processing, star elimination, and RSO association. Star elimination and RSO association use nearest neighbor association and thresholds on inertial frame-to-frame motion of observations to associate objects. Given a set of unresolved space images contiguous in time, the product of the algorithm presented is a set of measurements for orbit estimation.