Spatial Interpolation of Image Sequences Using Truncated Projections onto Convex Sets
Summary :
This paper presents a new method for image interpolation based on truncated projections onto convex sets (POCS). By using the convergence property to properly defined convex sets, the proposed algorithm can restore high frequency details in the original high resolution image. In order to apply the POCS method to the interpolation procedure, we first present a two-dimensional separable image degradation model for a low resolution imaging system. According to the model, we propose a truncated POCS-based spatial interpolation algorithm for image sequences. Experimental results with synthetic and real image sequence show that the proposed algorithm gives indiscernible interpolation performance compared with the conventional POCS-base algorithm, while it significantly reduces computational complexity and is suitable for processing image sequences.
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- IEICE TRANSACTIONS on Fundamentals Vol.E82-A No.6 pp.887-892
- Publication Date
- 1999/06/25
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- Type of Manuscript
- Special Section PAPER (Special Section of Papers Selected from 1998 International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC '98))
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Jeong Ho SHIN, Jung Hoon JUNG, Joon Ki PAIK, "Spatial Interpolation of Image Sequences Using Truncated Projections onto Convex Sets" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 6, pp. 887-892, June 1999, doi: .
Abstract: This paper presents a new method for image interpolation based on truncated projections onto convex sets (POCS). By using the convergence property to properly defined convex sets, the proposed algorithm can restore high frequency details in the original high resolution image. In order to apply the POCS method to the interpolation procedure, we first present a two-dimensional separable image degradation model for a low resolution imaging system. According to the model, we propose a truncated POCS-based spatial interpolation algorithm for image sequences. Experimental results with synthetic and real image sequence show that the proposed algorithm gives indiscernible interpolation performance compared with the conventional POCS-base algorithm, while it significantly reduces computational complexity and is suitable for processing image sequences.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_6_887/_p
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@ARTICLE{e82-a_6_887,
author={Jeong Ho SHIN, Jung Hoon JUNG, Joon Ki PAIK, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Spatial Interpolation of Image Sequences Using Truncated Projections onto Convex Sets},
year={1999},
volume={E82-A},
number={6},
pages={887-892},
abstract={This paper presents a new method for image interpolation based on truncated projections onto convex sets (POCS). By using the convergence property to properly defined convex sets, the proposed algorithm can restore high frequency details in the original high resolution image. In order to apply the POCS method to the interpolation procedure, we first present a two-dimensional separable image degradation model for a low resolution imaging system. According to the model, we propose a truncated POCS-based spatial interpolation algorithm for image sequences. Experimental results with synthetic and real image sequence show that the proposed algorithm gives indiscernible interpolation performance compared with the conventional POCS-base algorithm, while it significantly reduces computational complexity and is suitable for processing image sequences.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Spatial Interpolation of Image Sequences Using Truncated Projections onto Convex Sets
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 887
EP - 892
AU - Jeong Ho SHIN
AU - Jung Hoon JUNG
AU - Joon Ki PAIK
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1999
AB - This paper presents a new method for image interpolation based on truncated projections onto convex sets (POCS). By using the convergence property to properly defined convex sets, the proposed algorithm can restore high frequency details in the original high resolution image. In order to apply the POCS method to the interpolation procedure, we first present a two-dimensional separable image degradation model for a low resolution imaging system. According to the model, we propose a truncated POCS-based spatial interpolation algorithm for image sequences. Experimental results with synthetic and real image sequence show that the proposed algorithm gives indiscernible interpolation performance compared with the conventional POCS-base algorithm, while it significantly reduces computational complexity and is suitable for processing image sequences.
ER -
English
