• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.105-108
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• 1996

In this paper, we present an interpolation schema for image resolution enhancement using fuzzy logic. Proposed algorithm can recover both low and high frequency information in image data. In general, interpolation techniques are based on linear operators which are essentially details in the original image. In our fuzzy approach, the operator itself balances the strength of its sharpening and noise suppressing components according to the properties of the input image data. The proposed interpolation algorithm is performed in three step. First logic reasoning is applied to coarsely interpret the high frequency information. These results are combined to obtain the optical output. Using our approach, resolution of the original image can be applied to various kind of image processing topics such as image enhancement, subpixel edge detection, and filtering.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1488-1493
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• 2014

Shipping and logistics safety, security system is strengthening worldwide, the development of shipping and logistics safety security core technology for national security logistics system construction has been carried out. Interest in portable radiation detection device capable detecting gamma rays nuclides is increasing. In this paper, I would like to propose the study of resolution enhancement for accurate analysis of nuclides in the platform of the radiation detector portable with Cortex-A9.

• Phonetics and Speech Sciences
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• v.10 no.1
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• pp.33-38
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• 2018

Although deep neural network-based acoustic models have greatly improved the performance of automatic speech recognition (ASR), reverberation still degrades the performance of distant speech recognition in indoor environments. In this paper, we adopt the DenseNet, which has shown great performance results in image classification tasks, to improve the performance of reverberant speech recognition. The DenseNet enables the deep convolutional neural network (CNN) to be effectively trained by concatenating feature maps in each convolutional layer. In addition, we extend the concept of multi-resolution CNN to multi-resolution DenseNet for robust speech recognition in reverberant environments. We evaluate the performance of reverberant speech recognition on the single-channel ASR task in reverberant voice enhancement and recognition benchmark (REVERB) challenge 2014. According to the experimental results, the DenseNet-based acoustic models show better performance than do the conventional CNN-based ones, and the multi-resolution DenseNet provides additional performance improvement.

• Journal of Arbitration Studies
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• v.18 no.3
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• pp.91-116
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• 2008

E-Commerce constitutes an important part of all commercial activities. Online Alternative Dispute Resolution(Online ADR) or Online Dispute Resolution(ODR) is a new method of dispute, resolution which, is provided online. Most Online ADR services are alternatives to litigation. In this respect, they are the online transposition of the methods developed in the ADR movement such as negotiation, mediation and arbitration. But there are also online courts which are really normal courts in which the contesting parties communicate essentially online. This paper deals with the current operation of Online ADR and the ways to, activate it. They include (1) die establishment of legal stability regarding Online ADR, (2) the enhancement of system security in providing Online ADR services, (3) the introduction of Online ADR service platform for providing the various services through single window on a national, or global basis, and (4) the introduction of Online ADR online monitoring system for systematic dispute resolution services.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.663-668
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• 2011

Although multi-frame super resolution algorithm has many merits but it demands too much calculation time. Researches have shown that image processing time can be reduced using a CUDA(Compute unified device architecture) which is one of GPGPU(General purpose computing on graphics processing unit) models. In this paper, we show that the processing time of multi-frame super resolution algorithm can be reduced by employing the CUDA. It was applied not to the whole parts but to the largest time consuming parts of the program. The simulation result shows that using a CUDA can reduce an operation time dramatically. Therefore it can be possible that multi-frame super resolution algorithm is implemented in real time by using libraries of image processing algorithms which are made by a CUDA.

• ETRI Journal
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• v.32 no.3
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• pp.390-394
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• 2010

In this paper, we propose a new super-resolution technique based on interpolation of the high-frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The proposed technique uses DWT to decompose an image into different subband images. Then the high-frequency subband images and the input low-resolution image have been interpolated, followed by combining all these images to generate a new super-resolved image by using inverse DWT. The proposed technique has been tested on Lena, Elaine, Pepper, and Baboon. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques. For Lena's image, the PSNR is 7.93 dB higher than the bicubic interpolation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.167-176
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• 1999

The study about quantitative or qualitative analysis of object using digital image is being progressed actively with the development of the image medium and image process technique. But, it is very high that the dependency about image acquisition system of high resolution for image analysis of high accuracy and it is a equipment of high-price. In this study, I extracted the optimum condition of image enhancement by analyzing and enhancing the multiple images which were acquired by system of low-price. And I carried out the analysis of 3D accuracy by being applied the optimum condition of image enhancement. In the result of analysis of average 3D positioning error using law image and enhanced image which is acquired by applying the optimum condition of image enhancement, I could obtain the progressed accuracy about 10％ on the enhanced image.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.155-160
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• 2004

In this paper, we describe the results of a study on the edge enhancement of X-ray images by using their fuzzy system representation. A set of gray scale X-ray images was generated using the EGS4 computer code. An aluminum plate or a lead plate with three parallel strips taken out has been used as the object with the thickness and the width of the plate, and the gap between the two strips varied. We started with a comparative study on a set of the fuzzy sets for their applicability as the input fuzzy sets for the fuzzy system representation of the gray scale images. Then we describe how the fuzzy system is used to sharpen the edges. Our algorithm is based on adding the magnitude of the gradient not to the pixel value of concern but rather to the nearest neighboring pixel in the direction of the gradient. We show that this algorithm is better in maintaining the spatial resolution of the original image after the edge enhancement.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.178-185
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• 2021

Three-dimensional high-resolution magnetic resonance imaging (MRI) provides fine-level anatomical information for disease diagnosis. However, there is a limitation in obtaining high resolution due to the long scan time for wide spatial coverage. Therefore, in order to obtain a clear high-resolution(HR) image in a wide spatial coverage, a super-resolution technology that converts a low-resolution(LR) MRI image into a high-resolution is required. In this paper, we propose a super-resolution technique through filter learning based on information on the surrounding gradient information in 3D space from 3D MRI images. In the learning step, the gradient features of each voxel are computed through eigen-decomposition from 3D patch. Based on these features, we get the learned filters that minimize the difference of intensity between pairs of LR and HR images for similar features. In test step, the gradient feature of the patch is obtained for each voxel, and the filter is applied by selecting a filter corresponding to the feature closest to it. As a result of learning 100 T1 brain MRI images of HCP which is publicly opened, we showed that the performance improved by up to about 11% compared to the traditional interpolation method.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.169-181
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• 1997

In this paper, we propose and discuss about image enhancement techniques for MPEG-4. which represents very low bit-rate, content-based. and object-based hierarchical audio-visual coding standard. The proposed enhancement technique removes undesired artifacts arising in the compression procedure and increase resolution in both spatial and temporal domains. In order to remove undesired artifacts. we divide the MPEG-4 video algorithm in two parts: MPEG-2 like part and the new part. For removing artifacts caused by the first part. we adopt the conventional blocking artifacts algorithm developed for MPEG-2. On the other hand for removing artifacts caused by the second part. we provide a new degradation model. and propose the corresponding image restoration method. For increasing resolution of the MPEG-4 images, we propose a general framework of multichannel image interpolation process. which includes both spatial and temporal interpolations. As the MPEG-4 standard is under development. various sophisticated techniques are considered. but research on image enhancement techniques is relatively underestimated. By this reason. additional image enhancement techniques will become very important issue in realization phase of MPEG-4.