• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.84-95
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• 2011

In this paper, we present a deblocking algorithm that removes grid and staircase noises, which are called "blocking artifacts", occurred in the compressed satellite images. Particularly, the given satellite images are compressed with equal quantization coefficients in row according to region complexity, and more complicated regions are compressed more. However, this approach has a problem that relatively less complicated regions within the same row of complicated regions have blocking artifacts. Removing these artifacts with a general deblocking algorithm can blur complex and undesired regions as well. Additionally, the general filter lacks in preserving the curved edges. Therefore, the proposed algorithm presents an adaptive filtering scheme for removing blocking artifacts while preserving the image details including curved edges using the given quantization step size and content analysis. Particularly, WLFPCA (weighted lowpass filter using principle component analysis) is employed to reduce the artifacts around edges. Experimental results showed that the proposed method outperforms SA-DCT in terms of subjective image quality.

• Archives of design research
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• v.13 no.3
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• pp.29-38
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• 2000

Human has been living in the relation with diverse artifacts ranging from simple tools to complex systems. The relation is an interaction between user and product with input and output process to achieve a certain goals. Natural inter-connection is very important to this interaction. The visualized operation and the dear feedback of product play a critical role in making input and output distinct at both sides. So product innovation means removing mental and physical loads between product and user based on understanding and analyzing interaction. This study proposes the interaction grid as a framework to visualize the interaction. The interaction grid is the format to describe the input and output process between user and product. Modeling and analysis of interaction is based on the interaction grid. Finally, this study discusses the idea exploration method for product innovation with interaction grid, and develops prototype of interaction analysis system for supporting idea exploration.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.755-758
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• 2001

In this paper. Ive propose a postprocessing technique based on the theory of projection on convex sets(POCS) to reduce the blocking artifacts in HDTV decoded images. In BDCT of HDTV. the image is divided into a grid of non-overlapped 8 ${\times}$ 8 blocks. and then each block is coded separately. A block which is located one pixel apart from the grid of BDCT will include the boundary of the original 8 ${\times}$ 8 block. If the blocking artifact is Introduced alone the block boundary. this block will have different frequency characteristic from that of the original block. Thus, a comparison of frequency characteristics of these two overlapping blocks can detect the undesired high-frequency components mainly caused by the blocking artifact. By eliminating these undesired high-frequency components adaptively, robust smoothing projection operator can be obtained. Simulation results with real image sequences indicate that the proposed method performs better than conventional algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.213-224
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• 2010

In this paper, we propose an algorithm both geometric correction using a grid point image and radiometric adaptive projection that dependent upon the luminance of the input image and that of the background. This method projects and captures the grid point image then calculates the geometrically corrected position by difference between the two images. Next, to compensate color, a corrected image is calculated by the ratio divided luminance of an input image by luminance of arbitrary surface. In addition, we found the scaling factor which controls the contrast to avoid clipping error. At this time, the scaling factor is dependent on mean image lightness when background is determined. Experimental results show that the proposed method achieves good performance and is able to reduce the perceived color clipping and artifacts, better approximating the projection on a white screen.

• Investigative Magnetic Resonance Imaging
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• v.12 no.2
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• pp.123-130
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• 2008

Purpose : Motion effects in parallel magnetic resonance imaging (MRI) are investigated. Parallel MRI is known to be robust to motion due to its reduced acquisition time. However, if there are some involuntary motions such as heart or respiratory motions involved during the acquisition of the parallel MRI, motion artifacts would be even worse than those in conventional (non-parallel) MRI. In this paper, we defined several types of motions, and their effects in parallel MRI are investigated in comparisons with conventional MRI. Materials and Methods : In order to investigate motion effects in parallel MRI, 5 types of motions are considered. Type-1 and 2 are periodic motions with different amplitudes and periods. Type-3 and 4 are segment-based linear motions, where they are stationary during the segment. Type-5 is a uniform random motion. For the simulation, Cartesian and spiral grid based parallel and non-parallel (conventional) MRI are used. Results : Based on the motions defined, moving artifacts in the parallel and non-parallel MRI are investigated. From the simulation, non-parallel MRI shows smaller root mean square error (RMSE) values than the parallel MRI for the periodic (type-1 and 2) motions. Parallel MRI shows less motion artifacts for linear(type-3 and 4) motions where motions are reduced with shorter acquisition time. Similar motion artifacts are observed for the random motion (type-5). Conclusion : In this paper, we simulate the motion effects in parallel MRI. Parallel MRI is effective in the reduction of motion artifacts when motion is reduced by the shorter acquisition time. However, conventional MRI shows better image quality than the parallel MRI when fast periodic motions are involved.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.907-910
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• 2019

본 연구에서는 X-ray 영상에서 비산란 그리드 장치의 영향으로 인한 아티팩트를 제거하기 위하여 이산코사인변환(DCT: discrete cosine transform) 기반의 주파수 분석 기법과 딥러닝 네트워크의 학습 기법을 상호 보완적으로 결합하는 방법론을 제안한다. 피사체의 특성에 따라 다양하게 나타나는 그리드 라인의 억제 기능을 학습하기 위하여 서로 다른 특성을 반영하는 3 종류의 학습데이터를 생성한다. 학습에 사용되는 그리드 라인 영상의 타겟 데이터를 산출하기 위하여 DCT 기반의 밴드스톱 필터링 기법을 사용하였으며 학습데이터의 양적인 부족을 해결하기 위하여 패치 기반의 학습 방법을 적용하였다. 제안된 방법에 대해 기존의 방법과 비교하여 피사체 경계선 영역에서 발생하는 성능저하 현상, 분할의 가장자리에서 발생하는 블로킹 현상, 배경 영상에서의 성능저하 현상 등을 상대적으로 개선할 수 있음을 실험적으로 평가하였다.

• Journal of the Korean Society of Radiology
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• v.2 no.4
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• pp.5-9
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• 2008

Antiscatter grids are widely used in radiography to remove scattered X-rays and thus improve the image contrast. However, the use of grids makes moir$\acute{e}$ artifact in the digital image, and this can be a critical reason for a mistaken diagnosis. In this paper, we examined that moire artifacts are how to relate with grid frequency, pixel pitch and grid rotation angle. To experiment we prepared 6 grids having different line frequencies (4.0 to 8.5lines/mm) and tested with a DR imager having a $139{\mu}m{\times}139{\mu}m$ pixel size. In the result of this experiment, we could get data about moir$\acute{e}$ artifact that could be make solution to remove the line artifact for the successful use of the grid in digital radiography. The acquired data and theory through this experiment, are expected to make contribution to the elimination of moir$\acute{e}$ artifact in the DR system.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.715-727
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• 2024

During fast neutron imaging, besides the dark current noise and readout noise of the CCD camera, the main noise in fast neutron imaging comes from high-energy gamma rays generated by neutron nuclear reactions in and around the experimental setup. These high-energy gamma rays result in the presence of high-density gamma white spots (GWS) in the fast neutron image. Due to the microscopic quantum characteristics of the neutron beam itself and environmental scattering effects, fast neutron images typically exhibit a mixture of Gaussian noise. Existing denoising methods in neutron images are difficult to handle when dealing with a mixture of GWS and Gaussian noise. Herein we put forward a deep learning approach based on the Swin Transformer UNet (SUNet) model to remove high-density GWS-Gaussian mixture noise from fast neutron images. The improved denoising model utilizes a customized loss function for training, which combines perceptual loss and mean squared error loss to avoid grid-like artifacts caused by using a single perceptual loss. To address the high cost of acquiring real fast neutron images, this study introduces Monte Carlo method to simulate noise data with GWS characteristics by computing the interaction between gamma rays and sensors based on the principle of GWS generation. Ultimately, the experimental scenarios involving simulated neutron noise images and real fast neutron images demonstrate that the proposed method not only improves the quality and signal-to-noise ratio of fast neutron images but also preserves the details of the original images during denoising.

• Investigative Magnetic Resonance Imaging
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• v.15 no.1
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• pp.11-21
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• 2011

Purpose : Localization using MRI is difficult due to susceptibility induced artifacts caused by metal electrodes. Here we took an advantage of the B0 pattern induced by the metal electrodes by using an oblique-view imaging method. Materials and Methods : Metal electrode models with various diameters and susceptibilities were simulated to understand the aspect of field distortion. We set localization criteria for a turbo spin-echo (TSE) sequence usingconventional ($90^{\circ}$ view) and $45^{\circ}$ oblique-view imaging method through simulation of images with various resolutions and validated the criteria usingphantom images acquired by a 3.0T clinical MRI system. For a gradient-refocused echo (GRE) sequence, which is relatively more sensitive to field inhomogeneity, we used phase images to find the center of electrode. Results : There was least field inhomogeneity along the $45^{\circ}$ line that penetrated the center of the electrode. Therefore, our criteria for the TSE sequence with $45^{\circ}$ oblique-view was coincided regardless of susceptibility. And with $45^{\circ}$ oblique-view angle images, pixel shifts were bidirectional so we can detect the location of electrodes even in low resolution. For the GRE sequence, the $45^{\circ}$ oblique-view anglemethod madethe lines where field polarity changes become coincident to the Cartesian grid so the localization of the center coordinates was more facilitated. Conclusion : We suggested the method for accurate localization of electrode using $45^{\circ}$ oblique-view angle imaging. It is expected to be a novelmethodto monitoring an electrophysiological brain study and brain neurosurgery.