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Proceedings Paper

Image preprocessing for fast multiple-frame super-resolution reconstruction
Author(s): Shuqun Zhang
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Paper Abstract

Super-resolution reconstruction algorithms have been demonstrated to be very effective in enhancing image spatial resolution by combining several low-resolution images to yield a single high-resolution image. However, the high computational complexity has become a major obstacle for the use of super-resolution techniques in real time applications. Most previous computationally efficient super-resolution techniques have been focused on reducing the number of iterations due to the iterative nature of most super-resolution algorithms. In this paper, we propose a region-of-interest (ROI) image preprocessing technique to improve the processing speed of super-resolution reconstruction. To better integrate the preprocessing with super-resolution, the proposed ROI extraction technique is developed under the same statistical framework as super-resolution. Simulation results are provided to demonstrate the performance of the proposed method.

Paper Details

Date Published: 24 August 2006
PDF: 9 pages
Proc. SPIE 6312, Applications of Digital Image Processing XXIX, 63121S (24 August 2006); doi: 10.1117/12.682295
Show Author Affiliations
Shuqun Zhang, College of Staten Island, CUNY (United States)


Published in SPIE Proceedings Vol. 6312:
Applications of Digital Image Processing XXIX
Andrew G. Tescher, Editor(s)

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