• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.105.1-105.1
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• 2016

Many of the complex materials developed today derive their unique properties from the presence of multiple phases or from local variations in elemental concentration. Simply performing analysis of the bulk materials is not sufficient to achieve a true understanding of their physical and chemical natures. Secondary ion mass spectrometer (SIMS) has met with a great deal of success in material characterization. The basis of SIMS is the use of a focused ion beam to erode sample atoms from the selected region. The atoms undergo a charge exchange with their local environment, resulting in their conversion to positive and negative secondary ions. The mass spectrometric analysis of these secondary ions is a robust method capable of identifying elemental distribution from hydrogen to uranium with detectability of the parts per million (ppm) or parts per billion (ppb) in atomic range. Nano secondary ion mass spectrometer (Nano SIMS, Cameca Nano-SIMS 50) equipped with the reactive ion such as a cesium gun and duoplasmatron gun has a spatial resolution of 50 nm which is much smaller than other SIMS. Therefore, Nano SIMS is a very valuable tool to map the spatial distribution of elements on the surface of various materials In this talk, the surface imaging applications of Nano SIMS in KBSI will be presented.

• Journal of the Optical Society of Korea
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• v.19 no.4
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• pp.390-396
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• 2015

We propose a partial occlusion removal method for computational integral imaging reconstruction (CIIR) based on the usage of the exemplar based inpainting technique. The proposed method is an improved version of the original linear inpainting based CIIR (LI-CIIR), which uses the inpainting technique to fill in the data missing region. The LI-CIIR shows good results for images which contain objects with smooth surfaces. However, if the object has a textured surface, the result of the LI-CIIR deteriorates, since the linear inpainting cannot recover the textured data in the data missing region well. In this work, we utilize the exemplar based inpainting to fill in the textured data in the data missing region. We call the proposed method the neighboring elemental image exemplar based inpainting (NEI-exemplar inpainting) method, since it uses sources from neighboring elemental images to fill in the data missing region. Furthermore, we also propose an automatic occluding region extraction method based on the use of the mutual constraint using depth estimation (MC-DE) and the level set based bimodal segmentation. Experimental results show the validity of the proposed system.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.60-66
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• 2019

In this paper, we propose a new free-view three-dimensional (3D) computational reconstruction of integral imaging to improve the visual quality of reconstructed 3D images when low-resolution elemental images are used. In a conventional free-view reconstruction, the visual quality of the reconstructed 3D images is insufficient to provide 3D information to applications because of the shift and sum process. In addition, its processing speed is slow. To solve these problems, our proposed method uses a pixel rearrangement technique (PERT) with locally selective elemental images. In general, PERT can reconstruct 3D images with a high visual quality at a fast processing speed. However, PERT cannot provide a free-view reconstruction. Therefore, using our proposed method, free-view reconstructed 3D images with high visual qualities can be generated when low-resolution elemental images are used. To show the feasibility of our proposed method, we applied it to optical experiments.

• Journal of the Optical Society of Korea
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• v.14 no.2
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• pp.121-126
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• 2010

We analyze image visibility of a projection-type integral imaging system without diffuser, in terms of the fill factor, which is determined by the relationship between the exit pupil of the projection system and the size and the focal length of the elemental lens. High fill factor is a requirement for good visibility. Moreover, for psychological reasons, for the same fill factor, better visibility is accomplished using a relatively small elemental lens. In this paper, we study image visibility through basic experiments and results.

• Korean Journal of Optics and Photonics
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• v.19 no.6
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• pp.389-393
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• 2008

Enhanced reconstruction of heavy occluded objects was represented using estimation of variance in computational integral imaging. The system is analyzed to extract information of enhanced reconstruction from an elemental images set. To obtain elemental images with enhanced resolution, low focus error, and large depth of focus, synthetic aperture integral imaging (SAII) utilizing a digital camera has been adopted. The focused areas of the reconstructed image are varied with the distance of the reconstruction plane. When an occluded object is occluded heavily, an occluded object can not be reconstructed by removing the occluding object. To obtain reconstruction of the occluded object by remedying the effect of heavy occlusion, the statistical technique has been adopted.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.51-56
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• 2016

In this paper, we present a three-dimensional (3-D) automatic target recognition system based on optical integral imaging reconstruction. In integral imaging, elemental images of the reference and target 3-D objects are obtained through a lenslet array or a camera array. Then, reconstructed 3-D images at various reconstruction depths can be optically generated on the output plane by back-projecting these elemental images onto a display panel. 3-D automatic target recognition can be implemented using computational integral imaging reconstruction and digital nonlinear correlation filters. However, these methods require non-trivial computation time for reconstruction and recognition. Instead, we implement 3-D automatic target recognition using optical cross-correlation between the reconstructed 3-D reference and target images at the same reconstruction depth. Our method depends on an all-optical structure to realize a real-time 3-D automatic target recognition system. In addition, we use a nonlinear correlation filter to improve recognition performance. To prove our proposed method, we carry out the optical experiments and report recognition results.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.153-159
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• 2018

In this paper, we present a three-dimensional (3D) optical encryption technique for quick response (QR) code using computational synthesized integral imaging, computational volumetric reconstruction, and double random phase encryption. Two-dimensional (2D) QR code has many advantages, such as enormous storage capacity and high reading speed. However, it does not protect primary information. Therefore, we present 3D optical encryption of QR code using double random phase encryption (DRPE) and an integral imaging technique for security enhancement. We divide 2D QR code into four parts with different depths. Then, 2D elemental images for each part of 2D QR code are generated by computer synthesized integral imaging. Generated 2D elemental images are encrypted using DRPE, and our method increases the level of security. To validate our method, we report simulations of 3D optical encryption of QR code. In addition, we calculated the peak side-lobe ratio (PSR) for performance evaluation.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.388-394
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• 2014

In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.

• ETRI Journal
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• v.28 no.4
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• pp.521-524
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• 2006

In this letter, we propose a novel computational integral imaging reconstruction technique based on a lenslet array model. The proposed technique provides improvement of viewing images by extracting multiple pixels from elemental images according to ray tracing based on the lenslet array model. To show the feasibility of the proposed technique, we analyze it according to ray optics and present the experimental results.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07b
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• pp.1588-1591
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• 2005

In this paper, we propose novel computational reconstruction technique of three-dimensional objects in integral imaging by use of a lenslet array. We applied our technique to two different integral imaging systems according the distance between lenslet array and elemental image plane. Experimental results are presented and discussed as well.