• Smart Structures and Systems
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• v.30 no.3
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• pp.287-301
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• 2022

The machine-vision based structural displacement measurement methods are widely used due to its flexible deployment and non-contact measurement characteristics. The accuracy of vision measurement is directly related to the image resolution. In the field of computer vision, super-resolution reconstruction is an emerging method to improve image resolution. Particularly, the deep-learning based image super-resolution methods have shown great potential for improving image resolution and thus the machine-vision based measurement. In this article, we firstly review the latest progress of several deep learning based super-resolution models, together with the public benchmark datasets and the performance evaluation index. Secondly, we construct a binocular visual measurement platform to measure the distances of the adjacent corners on a chessboard that is universally used as a target when measuring the structure displacement via machine-vision based approaches. And then, several typical deep learning based super resolution algorithms are employed to improve the visual measurement performance. Experimental results show that super-resolution reconstruction technology can improve the accuracy of distance measurement of adjacent corners. According to the experimental results, one can find that the measurement accuracy improvement of the super resolution algorithms is not consistent with the existing quantitative performance evaluation index. Lastly, the current challenges and future trends of super resolution algorithms for visual measurement applications are pointed out.

• Current Optics and Photonics
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• v.6 no.3
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• pp.244-251
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• 2022

We introduce a spectral reconstruction method to enhance the spectral resolution in a static modulated Fourier-transform spectrometer. The optical-path difference and the interferogram in the focal plane, as well as the relationship of the interferogram and the spectrum, are discussed. Additionally, for better spectral reconstruction, applications of phase-error correction and apodization are considered. As a result, the transfer function of the spectrometer is calculated, and then the spectrum is reconstructed based on the relationship between the transfer function and the interferogram. The spectrometer comprises a modified Sagnac interferometer. The spectral reconstruction is conducted with a source with central wave number of 6,451 cm^-1 and spectral width of 337 cm^-1. In a conventional Fourier-transform method the best spectral resolution is 27 cm^-1, but by means of the spectral reconstruction method the spectral resolution improved to 8.7 cm^-1, without changing the interferometric structure. Compared to a conventional Fourier-transform method, the spectral width in the reconstructed spectrum is narrower by 20 cm^-1, and closer to the reference spectrum. The proposed method allows high performance for static modulated Fourier-transform spectrometers.

• Journal of the Korean Society of Radiology
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• v.12 no.1
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• pp.85-91
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• 2018

Computed tomography, which obtains section images from reconstruction process using projection images, has been applied to various fields. The spatial resolution of the reconstructed image depends on the device used in CT system, the object, and the reconstruction process. In this paper, we investigates the effect of the number of projection images and the pixel size of the detector on the spatial resolution of the reconstructed image under the parallel beam geometry. The reconstruction program was written in Visual C++, and the matrix size of the reconstructed image was $512{\times}512$. The numerical bar phantom was constructed and the Min-Max method was introduced to evaluate the spatial resolution on the reconstructed image. When the number of projections used in reconstruction process was small, artifact like streak appeared and Min-Max was also low. The Min-Max showed upper saturation when the number of projections is increased. If the pixel size of the detector is reduced to 50% of the pixel size of the reconstructed image, the reconstructed image was perfectly recovered as the original phantom and the Min-Max decreased as increasing the detector pixel size. This study will be useful in determining the detector and the accuracy of rotation stage needed to achieve the spatial resolution required in the CT system.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.266-274
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• 2007

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on top-down machine learning and recursive error back-projection. A face is represented by a linear combination of prototypes of shape and that of texture. With the shape and texture information of each pixel in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those that of texture by solving least square minimizations. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes. In addition, a recursive error back-projection procedure is applied to improve the reconstruction accuracy of high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution images captured at a distance.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.3 no.2
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• pp.65-71
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• 2017

To assess the effects of filter and reconstruction of Cu-64 PET data on Siemens scanner, the various reconstruction algorithm with various filters were assessed in terms of spatial resolution, non-uniformity (NU), recovery coefficient (RC), and spillover ratio (SOR). Image reconstruction was performed using filtered backprojection (FBP), 2D ordered subset expectation maximization (OSEM), 3D reprojection algorithm (3DRP), and maximum a posteriori algorithms (MAP). For the FBP reconstruction, ramp, butterworth, hamming, hanning, or parzen filters were used. Attenuation or scatter correction were performed to assess the effect of attenuation and scatter correction. Regarding spatial resolution, highest achievable volumetric resolution was $3.08mm^3$ at the center of FOV when MAP (${\beta}=0.1$) reconstruction method was used. SOR was below 4% for FBP when ramp, Hamming, Hanning, or Shepp-logan filter were used. The lowest NU (highest uniform) after attenuation & scatter correction was 5.39% when FBP (parzen filter) was used. Regarding RC, 0.9 < RC < 1.1 was obtained when OSEM (iteration: 10) was used when attenuation and scatter correction were applied. In this study, image quality of Cu-64 on Siemens Inveon PET was investigated. This data will helpful for the quantification of Cu-64 PET data.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2646-2651
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• 2021

A rectangular-shaped PET system with an adjustable gantry (AGPET) has been developed for imaging small animals. The AGPET system employs a new depth of interaction (DOI) method using a depth dependent reflector patterns and a new digital time pickoff method based on the pulse reconstruction method. To evaluate the performance of the AGPET, timing resolution, intrinsic spatial resolution and point source images were acquired. The timing resolution and intrinsic spatial resolution were measured using two detector modules and Na-22 gamma source. The PET images were acquired in two field of view (FOV) sizes, 30 mm and 90 mm, to demonstrate the characteristic of the AGPET. As a result of in the experiment results, the timing resolution was 0.9 ns using the pulse reconstruction method based on the bi-exponential model. The intrinsic spatial resolution was an average of 1.7 mm and the spatial resolution of PET images after DOI correction was 2.08 mm and 2.25 mm at the centers of 30 mm and 90 mm FOV, respectively. The results show that the proposed AGPET system provided higher sensitivity and resolution for small animal imaging.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.631-639
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• 2008

This study presents an approach to synthesize hyperspectral images of lower resolution at a higher resolution using the high resolution images acquired from a sensor of commercial satellites. The proposed method was applied to the reconstruction of EO-1 Hyperion images using the images acquired from IKONOS sensor. Based on the FitPAN-Mod pansharpening technique (Lee, 2008b), the hyperspectral images of 30m resolution were reconstructed at 1m resolution of IKONOS panchromatic image. In this study, the synthesized hyperspectral images of 50 bands, whose wavelengths range in the wavelength of panchromatic sensor, were generated from the three stages of high resolution reconstruction using FitPAN-Mod. The experimental results show that the proposed method effectively integrates the spatial detail of the panchromatic modality as well as the spectral detail of the hyperspectral one into the synthesized image. It indicates the proposed method has a potential as a technique to produce alternative images for the images that would have been observed from a hyperspectral sensor at the high resolution of commercial satellite images.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.11
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• pp.1-6
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• 2013

It is introduced the phase error sources of a incoherent hologram in incoherent triangular holography and derived the reconstruction image of point-source including the phase error in the lateral direction. From the reconstruction image of point-source, we analyzed the effect of phase error on the lateral resolution. When the phase retardation errors and azimuth angle error of a wave plate and a polarizer range from 0 to $2{\pi}/15$, the normalized intensities of reconstructed images are down by about 0.1% and 2.3%, respectively.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.715-717
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• 2004

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on a recursive error back-projection of top-down machine learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes, In addition to, a recursive error back-projection is applied to improve the accuracy of synthesized high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution one captured at a distance.

• Journal of radiological science and technology
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• v.22 no.1
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• pp.5-11
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• 1999

This paper reviews recent major activities on instrumentation and methodology of PET. The performance of the PET instrumentation can be expressed by four physical characteristics, 1) spatial resolution, 2) coincidence resolving time, 3) energy resolution, and 4) detection efficiency. The physical and technical aspects of PET systems are briefly discussed along with these characteristics. Toward high resolution PET the recent trend has been to design multiple rings of densely packed detector arrays with scintillators. In order to satisfy the sampling requirement in reconstruction, continuous detector units has been developed. Iterative image reconstruction algorithms have received considerable attention for improvement of both the sampling requirement and image quality toward the stationary PET. Better resolving time improves the maximum true coincidence rate, which is also increased with more detectors placed in coincidence with each other. It suggests that volume PET is promising for enhancement of detection efficiency. The scattered coincidence event rate may be reduced by using detectors with better energy resolution. The use of interplane septa, however, takes over improvement of energy resolution in 2D PET. Energy resolution becomes an important factor for image quality under the condition of septa removal such as volume PET. Toward full utilization of emitting photons, 3D reconstruction incorporating oblique rays has been studied, and volume reconstruction algorithms have been developed. Practical volume PET systems impose heavy burden not only to detector sets and coincidence circuits, but also to computers in the memory requirements and the data processing. In conclusion, there have been many ingenious methods in development of PET instrumentation, which are based on unique capability of PET. They will be expected to overcome technical limitations, and to approach the fundamental limits.