Reconstruction of a high resolution image from registration and restoration of low resolution images

B. C. Tom; A. K. Katsaggelos; N. P. Galatsanos

doi:10.1109/ICIP.1994.413745

Reconstruction of a high resolution image from registration and restoration of low resolution images

B. C. Tom, A. K. Katsaggelos, N. P. Galatsanos

MRC - Materials Research Center

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

48 Scopus citations

Abstract

In applications that demand highly detailed images, it is often not feasible nor sometimes possible to acquire images of such high resolution by just using hardware (high precision optics and charge coupled devices (CCDs)). Instead, image processing methods may be used to construct a high resolution image from multiple, degraded, low resolution images. It is assumed that the low resolution images have been sub-sampled and displaced by sub-pixel shifts. Therefore, the problem can be divided into three sub-problems: registration (estimating the shifts), restoration, and interpolation. This paper focuses on solving the first two sub-problems simultaneously, using the expectation-maximization (EM) algorithm. Experimental results are presented that demonstrate the effectiveness of this approach.

Original language	English (US)
Article number	413745
Pages (from-to)	553-557
Number of pages	5
Journal	Proceedings - International Conference on Image Processing, ICIP
Volume	3
DOIs	https://doi.org/10.1109/ICIP.1994.413745
State	Published - 1994
Event	The 1994 1st IEEE International Conference on Image Processing - Austin, TX, USA Duration: Nov 13 1994 → Nov 16 1994

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

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10.1109/ICIP.1994.413745

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title = "Reconstruction of a high resolution image from registration and restoration of low resolution images",

abstract = "In applications that demand highly detailed images, it is often not feasible nor sometimes possible to acquire images of such high resolution by just using hardware (high precision optics and charge coupled devices (CCDs)). Instead, image processing methods may be used to construct a high resolution image from multiple, degraded, low resolution images. It is assumed that the low resolution images have been sub-sampled and displaced by sub-pixel shifts. Therefore, the problem can be divided into three sub-problems: registration (estimating the shifts), restoration, and interpolation. This paper focuses on solving the first two sub-problems simultaneously, using the expectation-maximization (EM) algorithm. Experimental results are presented that demonstrate the effectiveness of this approach.",

author = "Tom, {B. C.} and Katsaggelos, {A. K.} and Galatsanos, {N. P.}",

note = "Publisher Copyright: {\textcopyright} 1994 IEEE.; The 1994 1st IEEE International Conference on Image Processing ; Conference date: 13-11-1994 Through 16-11-1994",

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T1 - Reconstruction of a high resolution image from registration and restoration of low resolution images

AU - Tom, B. C.

AU - Katsaggelos, A. K.

AU - Galatsanos, N. P.

PY - 1994

Y1 - 1994

N2 - In applications that demand highly detailed images, it is often not feasible nor sometimes possible to acquire images of such high resolution by just using hardware (high precision optics and charge coupled devices (CCDs)). Instead, image processing methods may be used to construct a high resolution image from multiple, degraded, low resolution images. It is assumed that the low resolution images have been sub-sampled and displaced by sub-pixel shifts. Therefore, the problem can be divided into three sub-problems: registration (estimating the shifts), restoration, and interpolation. This paper focuses on solving the first two sub-problems simultaneously, using the expectation-maximization (EM) algorithm. Experimental results are presented that demonstrate the effectiveness of this approach.

AB - In applications that demand highly detailed images, it is often not feasible nor sometimes possible to acquire images of such high resolution by just using hardware (high precision optics and charge coupled devices (CCDs)). Instead, image processing methods may be used to construct a high resolution image from multiple, degraded, low resolution images. It is assumed that the low resolution images have been sub-sampled and displaced by sub-pixel shifts. Therefore, the problem can be divided into three sub-problems: registration (estimating the shifts), restoration, and interpolation. This paper focuses on solving the first two sub-problems simultaneously, using the expectation-maximization (EM) algorithm. Experimental results are presented that demonstrate the effectiveness of this approach.

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JO - Proceedings - International Conference on Image Processing, ICIP

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T2 - The 1994 1st IEEE International Conference on Image Processing

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ER -

Reconstruction of a high resolution image from registration and restoration of low resolution images

Abstract

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