• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1477-1485
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• 2021

Recently, super-resolution has been intensively studied only on upscaling models with integer magnification. However, the need to expand arbitrary magnification is emerging in representative application fields of actual super-resolution, such as object recognition and display image quality improvement. In this paper, we propose a model that can support arbitrary magnification by using the weights of the existing integer magnification model. This model converts super-resolution results into the DCT spectral domain to expand the space for arbitrary magnification. To reduce the loss of high-frequency information in the image caused by the expansion by the DCT spectral domain, we propose a high-frequency attention network for arbitrary magnification so that this model can properly restore high-frequency spectral information. To recover high-frequency information properly, the proposed network utilizes channel attention layers. This layer can learn correlations between RGB channels, and it can deepen the model through residual structures.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.3-20
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• 2023

A computer-generated hologram (CGH) is a digitally calculated and recorded hologram in which the amplitude and phase information of an image is transmitted in free space. The CGH is in the form of a complex hologram, but it is converted into a phase-only hologram to display through a phase-only spatial light modulator (SLM). In this paper, in the process of including the amplitude information of an object in the phase information, when a technique that includes subsampling such as DPAC is used, we showed experimentally that the bandwidth of the phase-only hologram increases, and as a result, aliasing that was not present in the complex hologram can occur. In addition, it was experimentally shown that it is possible to generate a high-quality phase-only hologram by restricting the spatial frequency range even at a distance where the numerical reconstruction performance is degraded by aliasing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.129-132
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• 2022

Super-resolution is the process of converting a low-quality image into a high-quality image. This study was conducted using ESPCN. In a super-resolution deep neural network, different quality images can be output even when receiving the same input data according to the activation function that determines the weight when passing through each node. Therefore, the purpose of this study is to find the most suitable activation function for super-resolution by applying the activation functions ReLU, ELU, and Swish and compare the quality of the output image for the same input images. The CelebaA Dataset was used as the dataset. Images were cut into a square during the pre-processing process then the image quality was lowered. The degraded image was used as the input image and the original image was used for evaluation. As a result, ELU and swish took a long time to train compared to ReLU, which is mainly used for machine learning but showed better performance.

• Journal of the Korean Society of Radiology
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• v.82 no.1
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• pp.29-48
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• 2021

Diffusion-weighted magnetic resonance imaging (DW MRI) is a fast unenhanced technique that shows promise as a stand-alone modality for cancer screening and characterization. Currently, DW MRI may have lower sensitivity than that of dynamic contrast-enhanced MRI as a standalone modality for breast cancer detection but superior to that of mammography, which may provide a useful alternative for supplemental screening. Standardized acquisition and interpretation of DW MRI can improve the image quality and reduce the variability of the results. Furthermore, high-resolution DW MRI, with advanced techniques and postprocessing, will facilitate better detection and characterization of subcentimeter cancers and reduce false-negatives and false-positives. Future results from ongoing prospective multicenter clinical trials using standardized and optimized protocols will facilitate the use of DW MRI as a stand-alone modality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.801-814
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• 2004

In this paper, we propose a block adaptive binarization (BAB) using a modified quadratic filter (MQF) to binarize business card images acquired by personal digital assistant (PDA) cameras effectively. In the proposed method, a business card image is first partitioned into blocks of 8${\times}$8 and the blocks are then classified into character Hocks (CBs) and background blocks (BBs). Each classified CB is windowed with a 24${\times}$24 rectangular window centering around the CB and the windowed blocks are improved by the pre-processing filter MQF, in which the scheme of threshold selection in QF is modified. The 8${\times}$8 center block of the improved block is barbarized with the threshold selected in the MQF. A binary image is obtained tiling each binarized block in its original position. Experimental results show that the MQF and the BAB have much better effects on the performance of binarization compared to the QF and the global binarization (GB), respectively, for the test business card images acquired in a PDA. Also the proposed BAB using MQF gives binary images of much better quality, in which the characters appear much better clearly, over the conventional GB using QF. In addition, the binary images by the proposed BAB using MQF yields about 87.7% of character recognition rate so that about 32.0% performance improvement over those by the GB using QF yielding about 55.7% of character recognition rate using a commercial character recognition software.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.17-24
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• 2004

In this paper, the wavelet video coding using Low-Band-Shift(LBS) method and multiresolution motion estimation(MRME) is proposed. To overcome shift- variant property on wavelet coefficients, the LBS was proposed. LBS method previously has superior performance in terms of rate-distortion characteristic. However, this method needs more memory and computational complexity. Therefore to reduce computational complexity of video coding using LBS, we combine MRME with LBS. When mm is applied only, it has 7 times as much as existing method's motion vector because each subband has different motion vector using property of LBS, number of motion vector decreases. Proposed method decreases motion vector, and it decreases motion compensated Prediction error by detailed motion estimation. And then it shows better coding performance. Also this method reduces computational amount by smaller search area in higher resolution. The computational complexity of the proposed method is 12.1% of that of existing method at 3-level wavelet transform. The experimental results with the proposed method show about 0.2∼9.7% improvement of MAD performance in case of lossless coding, and 0.1∼2.0㏈ improvement of PSNR performance at 4he same bit rate in case of lossy coding.

• Journal of The Korean Society of Grassland and Forage Science
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• v.18 no.4
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• pp.317-322
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• 1998

This study was conducted to compare the DM intake, the digestibility, and the utilization of nitrogen and energy of Korean native goats, when fed on orchardgrass supplemented with alfalfa or birdsfoot trefoil. Experimental diets included three treatments: orchardgrass(OG) 100%, orchardgrass 6%+alfalfa(AA) 40%(OG+AA), and orchardgrass 60%+birdsfoot trefoil(BT) 40%(OG+BT). The CP content was higher for OG+AA and OG+BT diets than for OG diets(P<0.05). The NDF content was high in OG diets(P<0.05) and the lignin content was high in OG+BT diets(P<0.05), but the ADF content did not differ among all diets. The DM intake and the digestibility of OM and cellular constituents were higher for OG+AA diets than for OG diets(P<0.05), but the NDF and ADF digestibility were not significant difference among all diets. The apparently digested N was higher for OG+AA diets than for other diets(P<0.05). However, the retained N % and biological value were higher for OG+BT diets than for OG diets(P<0.05), but those were not differ between OG+AA and OG+BT diets. On the other hand, the utilization of DE and ME did not show the difference among all diets. Based on the results, the utilization of nitrogen and energy was more improved for legume supplemented diets(AA, BT) than for OG diets(P<0.05). Furthermore, the utilization of nitrogen was slightly more improved for OG+BT diets than for OG+AA diets, but the significantly difference was not observed.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.29-38
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• 2005

The fluid animation procedure consists of physical simulation and visual rendering. In the physical simulation of fluids, the most frequently used practices are the numerical simulation of fluid particles using particle dynamics equations and the continuum analysis of flow via Wavier-Stokes equation. Particle dynamics method is fast in calculation, but the resulting fluid motion is conditionally unrealistic The method using Wavier-Stokes equation, on the contrary, yields lifelike fluid motion when properly conditioned, yet the complexity of calculation restrains this method from being used in real-time applications. Global illumination is generally successful in producing premium-Duality rendered images, but is also excessively slow for real-time applications. In this paper, we propose a rapid fluid animation method incorporating enhanced particle dynamics simulation method and pre-integrated volume rendering technique. The particle dynamics simulation of fluid flow was conducted in real-time using Lennard-Jones model, and the computation efficiency was enhanced such that a small number of particles can represent a significant volume. For real-time rendering, pre-integrated volume rendering method was used so that fewer slices than ever can construct seamless inter-laminar shades. The proposed method could successfully simulate and render the fluid motion in real time at an acceptable speed and visual quality.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1154-1162
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• 2010

Because it is easy to implement the scalar quantizer, it is used in various video coding systems. Although the scalar quantizer with a large quantization stepsize can reduce the amount of data, it has disadvantage that the reconstructed picture quality is poor. In this paper, we propose an efficient method which improves the coding performance by maintaining original quantization stepsize and increasing the number of quantization reconstruction levels. Simultaneously, for the purpose of solving the problem of transmitting the added symbol informations which is used to indicate the region of quantizer reconstruction level as the number of quantizer reconstruction level is increased, we also suggest the method to reduce the added informations. Therefore, for the intra-coded picture of H.264 video coding system, we generate the huffman codes for the symbol informations of quantization reconstruction regions by 4${\times}$4(horizontal 4 pixels, vertical pixels) block unit. Furthermore, for the inter-coded picture, we also generate the huffman codes for the symbol informations of quantization reconstruction regions by 8${\times}$8 blocks and 4${\times}$4 blocks within a macroblock. Adopting this method of reducing the added information by increasing the number of quantization reconstruction region, It is shown that the coding performance can be improved at the same bitrate.

• Journal of radiological science and technology
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• v.39 no.2
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• pp.227-236
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• 2016

Dynamic positron emission tomography(dPET) is widely used medical imaging modality that can provide both physiological and functional neuro-image for diagnosing various brain disease. However, dPET images have low spatial-resolution and high noise level during spatio-temporal analysis (three-dimensional spatial information + one-dimensional time information), there by limiting clinical utilization. In order to overcome these issues for the spatio-temporal analysis, a novel computational technique was introduced in this paper. The computational technique based on singular value decomposition classifies multiple independent components. Signal components can be distinguished from the classified independent components. The results show that signal to noise ratio was improved up to 30% compared with the original images. We believe that the proposed computational technique in dPET can be useful tool for various clinical / research applications.