• 전자공학회논문지 IE
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• v.47 no.3
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• pp.7-13
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• 2010

In this paper, an efficient contrast enhancement algorithm using weighted histogram modification is proposed. For contrast enhancement, histogram equalization (HE) and histogram stretching (HS) are effective techniques. However, HE and HS may have excessive contrast enhancement. Proposed method using weighted histogram modification produces better natural and enhanced results than those of conventional contrast enhancement methods without artifacts.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.1035-1038
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• 2007

In this paper, we propose a color image improvement method. The proposed algorithms are classified with the adaptive contrast stretching method for contrast enhancement and the adaptive saturation enhancement method for saturation enhancement. The adaptive contrast stretching method is to compensate a significant change of brightness while luminance is processed. The adaptive saturation enhancement method inhibits its saturation from de-saturation and oversaturation while chrominance is processed. The proposed algorithms are focused on a preference color processing in order to generate better image quality than the algorithms focused on a uniform color processing for human vision.

• Journal of Korea Multimedia Society
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• v.22 no.7
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• pp.749-758
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• 2019

This paper proposes a data augmentation algorithm to improve the performance of DNN(Deep Neural Network) based speech enhancement. Many deep learning models are exploring algorithms to maximize the performance in limited amount of data. The most commonly used algorithm is the data augmentation which is the technique artificially increases the amount of data. For the effective data augmentation algorithm, we used a formant enhancement method that assign the different weights to the formant frequencies. The DNN model which is trained using the proposed data augmentation algorithm was evaluated in various noise environments. The speech enhancement performance of the DNN model with the proposed data augmentation algorithm was compared with the algorithms which are the DNN model with the conventional data augmentation and without the data augmentation. As a result, the proposed data augmentation algorithm showed the higher speech enhancement performance than the other algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.215-218
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• 2013

In this paper, we proposed a method for enhancement of color images with sky regions. The input image is converted into HSV space and then sky and non-sky regions are separated. For sky region, saturation enhancement is performed for each pixel based on the enhancement factor calculated from the average saturation of its local neighborhood. On the other hand, for the non-sky region, the enhancement is applied only on the luminance value (V) component of the HSV color image, which is performed in two steps. The luminance enhancement, which is also called as dynamic range compression, is carried out using nonlinear transfer function. Again, each pixel is further enhanced for the adjustment of the image contrast depending upon the center pixel and its neighborhood pixel values. At last, the original H and V component image and enhanced S component image for the sky region, and original H and S component image and enhanced V component image for the non-sky region are converted back to RGB image.

• Journal of Veterinary Clinics
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• v.37 no.5
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• pp.255-260
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• 2020

The purpose of this retrospective study was to describe the characteristics of magnetic resonance imaging (MRI) findings in dogs with meningoencephalitis of unknown etiology (MUE), and to evaluate the usefulness of meningeal enhancement. Thirty-two dogs were included in MUE group on the basis of clinical signs, MRI findings and cerebrospinal fluid (CSF) results, and for comparison of the meningeal enhancement, twenty-three dogs with normal MRI, normal CSF and no clinical sign were included in the control group. The evaluated MRI findings included lesion site, lesion number, signal intensity of each MRI sequence, mass effect, perilesional edema, contrast enhancement, and meningeal enhancement. The MUE was most frequently associated with multiple lesions (50%) with perilesional edema (72%) in forebrain (66%) that were hyperintense (92%) in T2W and FLAIR images. Of the meningeal enhancement, there was no significant difference between the control group and the MUE groups in the pachymeningeal enhancement. However, leptomeningeal (or both) enhancement was found relatively high proportion in the MUE group than in the control group (P < 0.001, Odd ratio = 10.26), and based on this result, leptomeningeal (or both) enhancement is considered to be significant finding for indicating MUE.

• Korean Journal of Culture and Social Issue
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• v.9 no.2
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• pp.101-126
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• 2003

The purpose of present study is to investigate what is the most important factor among personality, social relation perception, and cultural influence on North Korean Defectors' self-enhancement bias, and how their self-enhancement bias influences on their psychological adaptation in South Korea. To implement this, we compared the self-enhancement bias of South Korean undergraduates and North Korean Defector undergraduates, and social desirability, too. However, there was no significant result. Based on this outcome, we focused on 121 North Korean Defectors' self-enhancement bias mechanism. We found that personality and social relation perception factors influenced significantly on their self- enhancement bias and furthermore their self-enhancement bias affected on their psychological adaptation. In addition to this, we identified sex difference at this mechanism. That is, women showed the same pattern with the existing findings in the study of self-enhancement bias mechanism, but men showed somewhat different pattern.

• The Journal of Fisheries Business Administration
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• v.41 no.1
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• pp.1-24
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• 2010

The main goal of the study is to propose an objective and standardized evaluation system of stock enhancement programs. In order to achieve this goal, the study first suggested the need for stock enhancement program evaluation system through the review of current status and problems. Second, the study identified possible problems of the existing stock enhancement program evaluation by reviewing domestic and foreign evaluation systems. Finally the study proposed a new evaluation system and implementation plan of it. This study also classified the program evaluation criteria into ex-ante evaluation and ex-post evaluation according to the evaluation point in time, and applied the economic, political and technical feasibility tests into the evaluation of the stock enhancement program in order to solve the current problems of the evaluation. The evaluation process of the stock enhancement program is composed of an evaluation system design, estimation of weights using the analytical hierarchy process, design of estimation standard, conversion of scores and final summary of the evaluation. The central government takes the lead in the evaluation of the regional (metropolitan city or province) projects and the regional government is in charge of the evaluation of the local (city or county) projects. For the implementation of the ex-ante evaluation, either the regional or local governments ask for the evaluation and then submit an evaluation plan and other necessary documents to the upper level governments. The ex-post evaluation is then carried out by the upper level governments.

• Journal of electromagnetic engineering and science
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• v.5 no.2
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• pp.49-60
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• 2005

In this paper, an efficient performance enhancement scheme for an adaptive antenna array under the flat and the frequency-selective Rayleigh fadings is proposed. The proposed signal enhancement scheme is the modified linear signal estimator which combines the rank N approximation by reducing noise eigenvalues(RANE) and Toeplitz matrix approximation(TMA) methods into the linear signal estimator. The proposed performance enhancement scheme is performed by not only reducing the noise component from the signal-plus-noise subspace using RANE but also having the theoretical property of noise-free signal using TMA. Consequently, the key idea of the proposed performance enhancement scheme is to greatly enhance the performance of an adaptive antenna array by removing all undesired noise effects from the post-correlation received signal. The proposed performance enhancement scheme applies at the Wiener maximal ratio combining(MRC) method which has been widely used as the conventional adaptive antenna array. It is shown through several simulation results that the performance of an adaptive antenna array using the proposed signal enhancement scheme is much superior to that of a system using the conventional method under several environments, i.e., a flat Rayleigh fading, a fast frequency-selective Rayleigh fading, a perfect/imperfect power control, a single cell, and a multicell.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.360-367
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• 2002

In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1127-1136
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• 2016

Speech enhancement algorithm plays an important role in numerous speech signal processing applications. Over the last few decades, many algorithms have been studied for speech enhancement. The algorithms are based on spectral subtraction, Wiener filter, and subspace method etc. They have good performance of speech enhancement, but the performance can be deteriorated in specific noises or low SNR environment. In this paper, a new speech enhancement algorithms are proposed based on adaptive noise canceller. And the proposed algorithm improved performance of adaptive noise cancelling using 2-D binary mask. From objective experimental index, it is confirmed that the proposed algorithm is useful and has better performance than recently proposed speech enhancement algorithms.