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Proceedings Paper

Analysis and characterization of super-resolution reconstruction methods
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Paper Abstract

Reconstruction techniques exploit a first building process using Low-resolution (LR) images to obtain a "draft" High Resolution (HR) image and then update the estimated HR by back-projection error reduction. This paper presents different HR draft image construction techniques and shows methods providing the best solution in terms of final perceived/measured quality. The following algorithms have been analysed: a proprietary Resolution Enhancement method (RE-ST); a Locally Adaptive Zooming Algorithm (LAZA); a Smart Interpolation by Anisotropic Diffusion (SIAD); a Directional Adaptive Edge-Interpolation (DAEI); a classical Bicubic interpolation and a Nearest Neighbour algorithm. The resulting HR images are obtained by merging the zoomed LR-pictures using two different strategies: average or median. To improve the corresponding HR images two adaptive error reduction techniques are applied in the last step: auto-iterative and uncertainty-reduction.

Paper Details

Date Published: 16 May 2003
PDF: 9 pages
Proc. SPIE 5017, Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications IV, (16 May 2003); doi: 10.1117/12.476749
Show Author Affiliations
Sebastiano Battiato, STMicroelectronics (Italy)
Giovanni Gallo, Univ. degli Studi di Catania (Italy)
Massimo Mancuso, STMicroelectronics (Italy)
Giuseppe Messina, STMicroelectronics (Italy)
Filippo Stanco, Univ. degli Studi di Catania (Italy)

Published in SPIE Proceedings Vol. 5017:
Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications IV
Nitin Sampat; Ricardo J. Motta; Morley M. Blouke; Nitin Sampat; Ricardo J. Motta, Editor(s)

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