• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.763-768
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• 1999

The space variant imaging system which mimics the human beings visual system has some merits such as wide field-of-view, the low computational cost and the high accuracy in matching of correspondence points of stereo images. In this presentation, a visual servoing system based on the space variant imaging technique is proposed for the control of the rehabilitation robot arm. The position information of an object obtained by space variant imaging techniques is used for the visual servoing. According to the empirical data, the degree of correlation extracted by the space variant imaging technique is more accurate than that of the space invariant imaging technique.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.113-117
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• 2007

Sub-salt imaging is an unsolved hot issue in subsurface imaging area. We tested several important properties in imaging sub-salt structures to provide a clue to this problem. Reverse time migration using velocity models obtained by waveform inversion produced better results than that of stacking velocity analysis. Sub-salt imaging results were highly dependent on the size and shape of a salt structure. The results were not clear when the velocity of a salt structure is significantly higher than that of adjacent layers.

• Current Optics and Photonics
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• v.7 no.6
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• pp.655-664
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• 2023

Ghost imaging (GI) technology is developing rapidly, but there are inevitably some limitations such as the influence of atmospheric turbulence. In this paper, we study a ghost imaging system in atmospheric turbulence and use a gamma-gamma (GG) model to simulate the medium to strong range of turbulence distribution. With a compressed sensing (CS) algorithm and generative adversarial network (GAN), the image can be restored well. We analyze the performance of correlation imaging, the influence of atmospheric turbulence and the restoration algorithm's effects. The restored image's peak signal-to-noise ratio (PSNR) and structural similarity index map (SSIM) increased to 21.9 dB and 0.67 dB, respectively. This proves that deep learning (DL) methods can restore a distorted image well, and it has specific significance for computational imaging in noisy and fuzzy environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1598-1603
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• 2011

This paper describes an enhancement method for a computational pickup model. The conventional computational pickup model utilizes the ray-trace model and the pinhole model. The conventional model is very useful, however, it suffers from quality degradation of reconstructed images at long distances. To overcome the problem, we propose an accurate pickup model. The proposed model includes integration of the rays incoming to a sensor that generates a pixel, resulting in robustness on the Aliasing artifact. To show the effectiveness of the proposed method, experimental results are carried out. The results indicated that the proposed method is superior to the conventional method.

• Journal of information and communication convergence engineering
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• v.12 no.2
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• pp.89-96
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• 2014

Here, we present a review of the proposals and advances in the field of three-dimensional (3D) imaging acquisition and display made in the last century. The most popular techniques are based on the concept of stereoscopy. However, stereoscopy does not provide real 3D experience, and produces discomfort due to the conflict between convergence and accommodation. For this reason, we focus this paper on integral imaging, which is a technique that permits the codification of 3D information in an array of 2D images obtained from different perspectives. When this array of elemental images is placed in front of an array of microlenses, the perspectives are integrated producing 3D images with full parallax and free of the convergence-accommodation conflict. In the paper we describe the principles of this technique, together with some new applications of integral imaging.

• Journal of Magnetics
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• v.20 no.3
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• pp.308-311
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• 2015

We design a crisscrossed double-layer birdcage (DLBC) coil by modifying the coil geometry of a standard single-layer BC (SLBC) coil to enhance the homogeneity of transmitting magnetic flux density ($B_1{^+}$) along the main magnetic field ($B_0$)-direction for small-animal magnetic resonance imaging (MRI) at 300 MHz. The performance assessment of the crisscrossed DLBC coil is conducted by computational analysis with the finite-difference time domain method (FDTD) and compared with SLBC coil in terms of the $B_1$ and the $B_1{^+}$ distribution. As per the computational calculation studies, the mean value in the two-dimensional $B_1{^+}$ map obtained at the mid-axial slice with the proposed DLBC coil is slightly lower than that obtained with the SLBC coil, but the $B_1{^+}$ value of the DLBC coil in the outermost plane (40 mm away from the central plane) shows improvements of 19.3% and 24.8% over the SLBC coil $B_1{^+}$ value when simulating a spherical phantom and realistic mouse body modeling. These simulation results indicate that, the $B_1{^+}$ homogeneity along the z-direction was improved by using DLBC configuration. Our approach enables $B_1{^+}$ homogeneity improvement along the zdirection, and it can also be applied to ultra-high field (UHF) MRI systems.

• Proceedings of the Optical Society of Korea Conference
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• 2008.02a
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• pp.181-182
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• 2008

In this paper, we propose a volumetric computational reconstruction method by use of smart pixel mapping technique in the computational integral imaging in order to overcome the problem of resolution degradation. The experimental results are presented to show the usefulness of our proposed technique.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.383-389
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• 2016

This paper presents a novel automatic white balance (AWB) algorithm for consumer imaging devices. While existing AWB methods require reference white patches to correct color, the proposed method performs the AWB function using only an input image in two steps: i) white point detection, and ii) color constancy gain computation. Based on the dark channel prior assumption, a white point or region can be accurately extracted, because the intensity of a sufficiently bright achromatic region is higher than that of other regions in all color channels. In order to finally correct the color, the proposed method computes color constancy gain values based on the Y component in the XYZ color space. Experimental results show that the proposed method gives better color-corrected images than recent existing methods. Moreover, the proposed method is suitable for real-time implementation, since it does not need a frame memory for iterative optimization. As a result, it can be applied to various consumer imaging devices, including mobile phone cameras, compact digital cameras, and computational cameras with coded color.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.132-138
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• 2015

Enlarging the horizontal viewing angle is an important feature of integral imaging monitors. Thus far, the horizontal viewing angle has been enlarged in different ways, such as by changing the size of the elemental images or by tilting the lens array in the capture and reconstruction stages. However, these methods are limited by the microlenses used in the capture stage and by the fact that the images obtained cannot be easily projected into different displays. In this study, we upgrade our previously reported method, called SPOC 2.0. In particular, our new approach, which can be called SPOC 2.1, enlarges the viewing angle by increasing the density of the elemental images in the horizontal direction and by an appropriate application of our transformation and reshape algorithm. To illustrate our approach, we have calculated some high-viewing angle elemental images and displayed them on an integral imaging monitor.

• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.111-133
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• 2022

The exciting advancement related to the "modeling of digital human" in terms of a computational phantom for radiation dose calculations has to do with the latest hype related to deep learning. The advent of deep learning or artificial intelligence (AI) technology involving convolutional neural networks has brought an unprecedented level of innovation to the field of organ segmentation. In addition, graphics processing units (GPUs) are utilized as boosters for both real-time Monte Carlo simulations and AI-based image segmentation applications. These advancements provide the feasibility of creating three-dimensional (3D) geometric details of the human anatomy from tomographic imaging and performing Monte Carlo radiation transport simulations using increasingly fast and inexpensive computers. This review first introduces the history of three types of computational human phantoms: stylized medical internal radiation dosimetry (MIRD) phantoms, voxelized tomographic phantoms, and boundary representation (BREP) deformable phantoms. Then, the development of a person-specific phantom is demonstrated by introducing AI-based organ autosegmentation technology. Next, a new development in GPU-based Monte Carlo radiation dose calculations is introduced. Examples of applying computational phantoms and a new Monte Carlo code named ARCHER (Accelerated Radiation-transport Computations in Heterogeneous EnviRonments) to problems in radiation protection, imaging, and radiotherapy are presented from research projects performed by students at the Rensselaer Polytechnic Institute (RPI) and University of Science and Technology of China (USTC). Finally, this review discusses challenges and future research opportunities. We found that, owing to the latest computer hardware and AI technology, computational human body models are moving closer to real human anatomy structures for accurate radiation dose calculations.