High-resolution image reconstruction from rotated and translated low-resolution images with multisensors

You Wei Wen; Michael K. Ng; Wai Ki Ching

doi:10.1002/ima.20010

High-resolution image reconstruction from rotated and translated low-resolution images with multisensors

You Wei Wen^*, Michael K. Ng, Wai Ki Ching

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Journal article › peer-review

3 Citations (Scopus)

Abstract

We extend the multisensor work by Bose and Boo (1998) and consider the perturbations of displacement error that are due to both translation and rotation. The warping process is introduced to obtain the ideal low-resolution image, which is located at exactly horizontal and vertical shift. In this approach, the problem of high-resolution image reconstruction is turned into the problem of image restoration, and the system becomes spatially invariant rather than spatially variant in the original problem. An efficient algorithm is presented. Experimental results show that the proposed methods are quite effective, and they perform better than the bilinear image interpolation method.

Original language	English
Pages (from-to)	75-83
Number of pages	9
Journal	International Journal of Imaging Systems and Technology
Volume	14
Issue number	2
DOIs	https://doi.org/10.1002/ima.20010
Publication status	Published - 12 Aug 2004

Scopus Subject Areas

Electronic, Optical and Magnetic Materials
Software
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

User-Defined Keywords

High resolution
Low resolution
Reconstruction

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10.1002/ima.20010

Cite this

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abstract = "We extend the multisensor work by Bose and Boo (1998) and consider the perturbations of displacement error that are due to both translation and rotation. The warping process is introduced to obtain the ideal low-resolution image, which is located at exactly horizontal and vertical shift. In this approach, the problem of high-resolution image reconstruction is turned into the problem of image restoration, and the system becomes spatially invariant rather than spatially variant in the original problem. An efficient algorithm is presented. Experimental results show that the proposed methods are quite effective, and they perform better than the bilinear image interpolation method.",

keywords = "High resolution, Low resolution, Reconstruction",

author = "Wen, {You Wei} and Ng, {Michael K.} and Ching, {Wai Ki}",

note = "Chinese Academy of Science. Grant Number: KZCX1-SW-18 Guangdong Natural Science Foundation. Grant Number: 032475 Research Grants Council. Grant Numbers: 7130/02P, 7046/03P HKU CRCG. Grant Numbers: 10203907, 10204437, 10203501 Publisher Copyright: {\textcopyright} 2004 Wiley Periodicals, Inc.",

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AU - Wen, You Wei

AU - Ng, Michael K.

AU - Ching, Wai Ki

N1 - Chinese Academy of Science. Grant Number: KZCX1-SW-18 Guangdong Natural Science Foundation. Grant Number: 032475 Research Grants Council. Grant Numbers: 7130/02P, 7046/03P HKU CRCG. Grant Numbers: 10203907, 10204437, 10203501 Publisher Copyright: © 2004 Wiley Periodicals, Inc.

PY - 2004/8/12

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N2 - We extend the multisensor work by Bose and Boo (1998) and consider the perturbations of displacement error that are due to both translation and rotation. The warping process is introduced to obtain the ideal low-resolution image, which is located at exactly horizontal and vertical shift. In this approach, the problem of high-resolution image reconstruction is turned into the problem of image restoration, and the system becomes spatially invariant rather than spatially variant in the original problem. An efficient algorithm is presented. Experimental results show that the proposed methods are quite effective, and they perform better than the bilinear image interpolation method.

AB - We extend the multisensor work by Bose and Boo (1998) and consider the perturbations of displacement error that are due to both translation and rotation. The warping process is introduced to obtain the ideal low-resolution image, which is located at exactly horizontal and vertical shift. In this approach, the problem of high-resolution image reconstruction is turned into the problem of image restoration, and the system becomes spatially invariant rather than spatially variant in the original problem. An efficient algorithm is presented. Experimental results show that the proposed methods are quite effective, and they perform better than the bilinear image interpolation method.

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High-resolution image reconstruction from rotated and translated low-resolution images with multisensors

Abstract

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