• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.4
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• pp.363-370
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• 2017

In this paper, we proposed a low-complexity speech enhancement algorithm based on a improved minima controlled recursive averaging (IMCRA) and log minimum mean square error (logMMSE). The IMCRA algorithm track the minima value of input power within buffers in local window and identify the speech presence using ratio between input power and its minima value. In this process, many number of operations are required. To reduce the number of operations of IMCRA algorithm, minima value is tracked using time-varying frequency-dependent smoothing based on speech presence probability. The proposed algorithm enhanced speech quality by 2.778%, 3.481%, 2.980% and 2.162% in 0, 5, 10 and 15dB SNR respectively and reduced computational complexity by average 9.570%.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.155-163
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• 2010

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on-board the NASA's Terra spacecraft provides along-track digital stereo image data at 15m resolution with a base-height ratio 0.6. Automated stereocorrelation procedure was implemented using the ENVI 4.1 software to derive DEMs with $15m{\times}15m$ in 43km long and 50km wide area using the ASTER stereo images. The accuracy of DEMs was analyzed in comparison with those which were obtained from digital topographic maps of 1:25,000 scale. Results indicate that RMSE in elevation between ${\pm}7$ and ${\pm}20m$ could be achieved. Excluding cloud, water and building areas as the factors which make RMSE value exceeding 10m, the accuracy of DEMs showed RMSE of ${\pm}5.789m$. Therefore for the purpose of elevating accuracy of topographic information, we intended to detect the cloud areas and shadow areas by a landcover classification method, remove those areas on the ASTER DEM and then replace with those areas detached from the cartographic DEM by band math.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.120-131
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• 2020

Water body detection using remote sensing based on machine interpretation of satellite image is efficient for managing water resource, drought and flood monitoring. In this study, water body detection with SAR satellite image based on machine learning was performed. However, non water body area can be misclassified to water body because of shadow effect or objects that have similar scattering characteristic comparing to water body, such as roads. To decrease misclassifying, 8 combination of morphology open filtered band, DEM band, curvature band and Cosmo-SkyMed SAR satellite image band about Mokpo region were trained to semantic segmentation machine learning models, respectively. For 8 case of machine learning models, global accuracy that is final test result was computed. Furthermore, concordance rate between landcover data of Mokpo region was calculated. In conclusion, combination of SAR satellite image, morphology open filtered band, DEM band and curvature band showed best result in global accuracy and concordance rate with landcover data. In that case, global accuracy was 95.07% and concordance rate with landcover data was 89.93%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.11 no.1
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• pp.55-60
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• 1993

Forest occupied a part of natural ecosystem carries out a role of purifying air, preserving water resource, prevention of the breeding and extermination, recreation areas and etc that preserve and for me one's living environment. In this study, the classification for management of this forest is performed with Landsat TM Image. The classes are decided needle-leaf trees, broad-leaf trees, farming land and grass land, and water. When the TM digital images are classified on computer, water is represented in 7∼13 D.N. of 4th band. But the others is appeared similar mostly specific values so that must be done image processing. When the images compounded 2ed band and 3ed band are processed with ratio of enhancement. Needle-leaf treas is represented in l18∼136 D.N. of 1st band, broad-leaf trees in 72∼91 D.N. of 3ed band, farm land and glass land in 96∼120 of 3ed band. Forest Information is classified with M.L.C, an image classification method. The errors of needle-leaf trees, broad-leaf trees, farm land and grass land, and water are appeared each －7.43, ＋1.89,＋7.58 and －2.04 as compared the digital image with investigation on the scene. Finally, these results are useful for classification of forest vegetation with Landsat TM Image.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.33-41
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• 2001

Currently, the compression is one of the most important technology in multimedia society. Audio files arc rapidly propagated throughout internet Among them, the most famous one is MP-3(MPEC-1 Laver3) which can obtain CD tone from 128Kbps, but tone quality is abruptly down below 64Kbps. MPEC-II AAC(Advanccd Audio Coding) is not compatible with MPEG 1, but it has high compression of 1.4 times than MP 3, has max. 7.1 and 96KHz sampling rate. In this paper, we propose an algorithm that decreased the capacity of AAC encoding computation but increased the processing speed by optimizing psychoacoustic model which has enormous amount of computation in MPEG 2 AAC encoder. The optimized psychoacoustic model algorithm was implemented by C++ language. The experiment shows that the psychoacoustic model carries out FFT(Fast Fourier Transform) computation of 3048 point with 44.1 KHz sampling rate for SMR(Signal to Masking Ratio), and each entropy value is inputted to the subband filters for the control of encoder block. The proposed psychoacoustic model is operated with high speed because of optimization of unpredictable value. Also, when we transform unpredictable value into a tonality index, the speed of operation process is increased by a tonality index optimized in high frequency range.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.311-321
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• 2009

This paper proposes an efficient frequency offset estimation algorithm for MB-OFDM based UWB systems. The time-frequency interleaving in MB-OFDM extends the time-interval between two transmitted OFDM symbols in the same sub-band. The extended time-interval causes not only the degradation of the system performance by reducing frequency offset estimation range, but also the increase of the hardware complexity by requiring the larger number of storing samples. The proposed estimation algorithm expands the estimation range by applying the proposed sign detection scheme. Simulation results show that the estimation range is increased above 30 ppm compared with a conventional auto-correlation based scheme. The estimation is performed on only one sub-band, and the frequency offsets of the others are calculated by relation to center frequency. This way reduced the number of the storing samples by about l/3. The frequency offset estimator with the proposed algorithm was designed into the architecture which minimizes hardware overhead by time-sharing operators and memory units, and which was synthesized to gate-level circuits using $0.13{\mu}m$ CMOS technology, and the total gates were about 47K.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.13-17
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• 2009

고해상도 위성영상의 분류 기술은 최근 가장 활발히 연구되고 있는 분야 중 하나로 텍스쳐(texture), NDVI, PCA 영상 등 다양한 전처리 정보들을 추출하고 이를 멀티스펙트럴 밴드와 조합하여 분류 정확도를 높이는 기술을 개발하는 연구들이 주를 이루고 있다. 고해상도 위성영상에서 건물의 그림자와 옆벽면의 폐색 지역은 개체 추출 및 분류를 방해하는 주된 요인이 되며, 다양한 형태와 분광특성을 갖는 개개의 건물은 자동 분류 과정을 통해 제대로 식별되지 않는다는 한계를 갖는다. 이에 본 연구에서는 KOMPSAT-2 단영상으로부터 효율적으로 건물 정보 및 토지피복을 분류하기 위하여, 추출된 건물 정보를 바탕으로 건물의 그림자와 폐색지역을 보정한 후 비건물 지역에 대한 분류를 수행하여 분류 정확도를 높이고자 하였다. 우선 삼각벡터구조 기반의 반자동 인터페이스를 이용하여 건물의 3차원 모델 및 그림자 영역을 추출하고 이로부터 추출된 그림자 영역을 효과적으로 보정하기 위해 반복 선형회귀 연산을 이용한 그림자 보정을 수행한 후 inpainting 기법을 건물 폐색영역 복원에 적용하여 영상의 품질을 향상시켰다. 이러한 과정을 통해 도심 지역의 영상 분석에 있어 가장 큰 오차를 일으키는 인공물의 그림자와 폐색에 의한 오차를 최소화한 후 분류에 적용하여 이를 보정 전 영상을 이용한 분류 결과와 비교하였다.

• Economic and Environmental Geology
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• v.43 no.5
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• pp.467-475
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• 2010

The Landsat and ASTER data have been used in mineralogical and lithological studies, and they have also proved to be useful tool in the initial steps for mineral exploration throughout Nevada mining district, US. Huge pyrophyllite quarry mines, including Jungang, Samsung, Kyeongju, and Naenam located in the southeastern part of Gyeongsang Basin. The geology of study area consists mainly of Cretaceous volcanic rocks, which belong into Cretaceous Hayang and Jindong Group. They were intruded by Bulgugsa granites, so called Sannae-Eonyang granites. To extraction of Ratio model for pyrophyllite deposits, tuffaceous rock and pyrophyllite ores from the Jungang mine used in reflectance spectral analysis and these results were re-sampled to Landsat and ASTER bandpass. As a result of these processes, the pyrophyllite ores spectral features show strong reflectance at band 5, whereas strong absorption at band 7 in Landsat data. In the ASTER data, the pyrophyllite ores spectral features show strong absorption at band 5 and 8, whereas strong reflectance at band 4 and 7. Based on these spectral features, as a result of application of $Py_{Landsat}$ model to hydrothermal alteration zone and other exposed sites, the DN values of two different areas are 1.94 and 1.19 to 1.49, respectively. The differences values between pyrophyllite deposits and concrete-barren area are 0.472 and 0.399 for $Py_{ASTER}$ model, 0.452 and 0.371 for OHIb model, 0.365 and 0.311 for PAK model, respectively. Thus, $Py_{ASTER}$ and $Py_{Landsat}$ model proposed from this study proved to be more useful tool for the extraction of pyrophyllite deposits relative to previous models.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1605-1613
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• 2020

The tidal channel is a coastal sedimentary terrain that plays the most important role in the formation and development of tidal flats, and is considered a very important index for understanding and distribution of tidal flat sedimentation/erosion terrain. The purpose of this study is to understand the changes in tidal channels by a period after the opening of the floodgate of the seawall in the reclaimed land of Sihwa Lake using KOMPSAT high-resolution multispectral satellite image data and to evaluate the applicability and efficiency of high-resolution satellite images. KOMPSAT 2 and 3 images were used for extraction of the tidal channels' lineaments in 2009, 2014, and 2019 and were applied to supervised classification method based on Principal Component Analysis (PCA), Artificial Neural Net (ANN), Matched Filtering (MF), and Spectral Angle Mapper (SAM) and band ratio techniques using Normalized Difference Water Index (NDWI) and MF/SAM. For verification, a numerical map of the National Geographic Information Service and Landsat 7 ETM+ image data were utilized. As a result, KOMPSAT data showed great agreement with the verification data compared to the Landsat 7 images for detecting a direction and distribution pattern of the tidal channels. However, it has been confirmed that there will be limitations in identifying the distribution of tidal channels' density and providing meaningful information related to the development of the sedimentary process. This research is expected to present the possibility of utilizing KOMPSAT image-based high-resolution remote exploration as a way of responding to domestic intertidal environmental issues, and to be used as basic research for providing multi-platform-image-based convergent thematic maps and topics.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.137-144
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• 2005

In this paper, the extraction method of the edge histogram directly using wavelet coefficients in the wavelet domain for JPEG2000 images is proposed. MPEG-7 Edge Histogram Descriptor(EHD) extracts edge histogram in the spacial domain. This algorithm has much multiplication and addition for the edge extraction because it needs the decoding processing. However because the proposed algorithm extracts the edge histogram in the wavelet domain, it doesn't need the decoding processing and it decreases multiplication and addition. The Discrete Wavelet Transform(DWT) is a standard transform in JPEG2000. The proposed algorithm uses Le Gall 5/3 filter in JPEG2000 and odd coefficients in LH2 and HL2 sub-band. The edge direction can be decided to use rate of HL2 and LH2 odd coefficients. According to experiments, there is no difference of the efficiency between EHD and the proposed algorithm And the proposed algorithm is much better than EHD for multiplication and addition in the edge extraction of images.