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A Super-Resolution Imaging Method Based on Dense Subpixel-Accurate Motion Fields

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Abstract

A super-resolution imaging method suitable for imaging objects moving in a dynamic scene is described. The primary operations are performed over three threads: the computation of a dense inter-frame 2-D motion field induced by the moving objects at a sub-pixel resolution in the first thread. Concurrently, each video image frame is enlarged by the cascode of an ideal low-pass filter and a higher rate sampler, essentially stretching each image onto a larger grid. Then, the main task is to synthesize a higher resolution image from the stretched image of the first frame and that of the subsequent frames subject to a suitable motion compensation. A simple averaging process and/or a simplified Kalman filter may be used to minimize the spatio-temporal noise, in the aggregation process. The method is simple and can take advantage of common MPEG-4 encoding tools. A few experimental cases are presented with a basic description of the key operations performed in the over all process.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Vietnam National University, Hanoi, 144 Xuan Thuy, Vietnam

    Ha V. Le

  2. Department of Electrical and Computer Engineering, Air Force Institute of Technology, Wright-Patterson AFB, OH, 45433-7765

    Guna Seetharaman

Authors
  1. Ha V. Le
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  2. Guna Seetharaman
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Correspondence to Ha V. Le.

Additional information

Ha Vu Le is currently with the Robotics Laboratory, Department of Electrical and Computer Engineering, Vietnam National University, Hanoi. He received the B.S. degree in Computer Science from the Hanoi University of Technology in 1993. He was employed at the Institute of Information Technology, Vietnam, from 1993 to 1997, as a researcher, working to develop software tools and applications in the areas of Computer Graphics and Geographical Information Systems. He received the M.S. degree from the California State Polytechnic University, Pomona, in 2000, and the Ph.D. degree from the University of Louisiana at Lafayette in 2003, both in Computer Science. His research interests include Computer Vision, Robotics, Image Processing, Computer Graphics, and Neural Networks.

Guna Seetharaman is currently with The Air Force Institute of Technology, where he is an associate professor of computer engineering and computer science. He has been with the Center for Advanced Computer Studies, University of Louisiana at Lafayette since 1988. He was also a CNRS Visiting Professor at The Institute for Electronics Fundamentals, University of Paris XI, His current focus is on Three Dimensional Displays, Digital Light Processing, Nano and Micro sensors for imaging applications. He has earned his Ph.D. in electrical and computer engineering in 1988 from University of Miami FL; M.Tech in Electrical Engineeing (1982) from Indian Institute of Technology, Chennai; and, B.E. Electronics and Telecommunications from University of Madras, Guindy Campus. He served as the Technical Program Chair, and The local organizations chair for The Sixth IEEE Workshop on Computer Architecture for Machine Perception, New Orleans, May 2004; and Technical Committee member and editor for The Second International DOE-ONR-NSF Workshop on Foundations of Decision and Information Fusion, Washington DC, 1996. He served on the program committees of various International Conferences in the areas of Image Processing and Computer Vision. His works have been widely cited in industry and research. He is a member of Tau Beta Pi, Eta Kappa Nu, ACM, and IEEE.

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Le, H.V., Seetharaman, G. A Super-Resolution Imaging Method Based on Dense Subpixel-Accurate Motion Fields. J VLSI Sign Process Syst Sign Image Video Technol 42, 79–89 (2006). https://doi.org/10.1007/s11265-005-4167-8

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  • DOI: https://doi.org/10.1007/s11265-005-4167-8

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