Multiframe Super-Resolution Reconstruction of Small Moving Objects

Multiframe super-resolution (SR) reconstruction of small moving objects against a cluttered background is difficult for two reasons: a small object consists completely of "mixed" boundary pixels and the background contribution changes from frame-to-frame. We present a solution to this problem that greatly improves recognition of small moving objects under the assumption of a simple linear motion model in the real-world. The presented method not only explicitly models the image acquisition system, but also the space-time variant fore- and background contributions to the "mixed" pixels. The latter is due to a changing local background as a result of the apparent motion. The method simultaneously estimates a subpixel precise polygon boundary as well as a high-resolution (HR) intensity description of a small moving object subject to a modified total variation constraint. Experiments on simulated and real-world data show excellent performance of the proposed multiframe S...

• Type: Journal
• Year: 2010
• Where: TIP
• Authors: Adam W. M. van Eekeren, Klamer Schutte, Lucas J. van Vliet
• Keywords: Background Contribution Changes, Background Contributions, Education, Small Moving Object, TIP 2010