• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.461-471
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• 2012

The purpose of this paper is to visualize the housing market dynamics with ESDA (Exploratory Spatial Data Analysis) using MATLAB toolbox, in terms of the modeling housing market dynamics in the Busan Metropolitan City. The data are used the real housing price transaction records in Busan from the first quarter of 2006 to the second quarter of 2009. Hedonic house price model, which is not reflecting spatial autocorrelation, has been a powerful tool in understanding housing market dynamics in urban housing economics. This study considers spatial autocorrelation in order to improve the traditional hedonic model which is based on OLS(Ordinary Least Squares) method. The study is, also, investigated the comparison in terms of $R^2$, Sigma Square(${\sigma}^2$), Likelihood(LR) among spatial econometrics models such as SAR(Spatial Autoregressive Models), SEM(Spatial Errors Models), and SAC(General Spatial Models). The major finding of the study is that the SAR, SEM, SAC are far better than the traditional OLS model, considering the various indicators. In addition, the SEM and the SAC are superior to the SAR.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.123-131
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• 2005

Among the digital halftoning, the error diffusion halftoning gives better subjective quality than other halftoning techniques. But it also makes edges of objects blurred. To overcome the defect, this paper proposes the modified error diffusion halftoning algorithm to enhance the edges using the spatial perceptual properties of the human visual system. Using the properties that the human eyes perceive not the pixel's luminance itself but the local average luminance and the information that human eyes perceive spatial variation, the proposed method computes information of edge enhancement(IEE). The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. Also this paper proposes the technique that the coefficients of the error diffusion filter are adapted according to the correlation among color components. The computer simulation results show that the proposed method produces finer halftoning images than conventional methods due to the enhanced edges. And the proposed method also preserves similar in edges to original image and reduces some defects such as color impulse and false contours.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1631-1637
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• 2019

In this paper, we propose a low-complexity robust maximum likelihood (ML) receiver for generalized spatial modulation. The proposed receiver performs the transmit antenna partition to lower the computational loads. After we divide the transmit antenna combinations into two parts, one of which is "the likely TAC part," and the other of which is "the unlikely TAC part", based on the minimum mean square error (MMSE) filtering output. We first perform the maximum likelihood detection only in the likely TAC part. Then we evaluate the reliability of the solution found in the first search, and based its reliability we decide whether we continue the search in the unlikely TAC part. This partitioned search strategy maintains the performance of the conventional robust maximum likelihood receiver and simultaneously lowers computational loads. Through simulation, we found that our newly-proposed receiver achieves considerable gains over the conventional robust ML detector in terms of the computational loads while providing almost the same performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.306-314
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• 2004

Some receiver(and most transmit) beamforming algorithms with an array antenna at a cellular CDMA base stations require accurate internal and external calibrations. The external calibration, which usually needs to be done only once, determines the array manifolds, i.e. the complex response of each antenna as a function of DOA(Directions of Arrival). The internal calibrations are necessary because characteristics of RF/IF circuity of each receiver chain vary differently in response to temperature or humidity changes. We propose an iterative subspace-based calibration algorithm for an asynchronous CDMA-based antenna away in the presence of unknown gain and phase error is presented. We verify the subspace-based calibration algorithms by performing the experiment using measured data. Also, we propose an efficient algorithm using the simulated annealing technique. This algorithm overcomes the problem of the initial guessing in the subspace-based approach.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.125-132
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• 2017

Even after applying an image registration, Very High Resolution (VHR) multi-temporal images acquired from different optical satellite sensors such as IKONOS, QuickBird, and Kompsat-2 show a local misalignment due to dissimilarities in sensor properties and acquisition conditions. As the local misalignment, also referred to as Registration Noise (RN), is likely to have a negative impact on multi-temporal information extraction, detecting and reducing the RN can improve the multi-temporal image processing performance. In this paper, an approach to fine registration between VHR multi-temporal images by considering local distribution of RN is proposed. Since the dominant RN mainly exists along boundaries of objects, we use edge information in high frequency regions to identify it. In order to validate the proposed approach, datasets are built from VHR multi-temporal images acquired by optical satellite sensors. Both qualitative and quantitative assessments confirm the effectiveness of the proposed RN-based fine registration approach compared to the manual registration.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.233-240
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• 2004

Most of hydrological analyses in the field of water resources are launched by gathering and analyzing rainfall data. Several methods have been developed to estimate areal rainfall from point rainfall data and to fill missing or ungaged data. Thiessen and Reciprocal Distance Squared(RDS) methods whose parameters are only dependent on inter-station distance are classical work in hydrology, but these techniques do not provide a continuous representation of the hydrologic process involved. In this study, kriging technique was applied to rainfall analysis in Nakdong river basin in order to complement the defects of these classical methods and to reflect spatial characteristics of regional rainfall. After spatial correlation and semi-variogram analyses were performed to perceive regional rainfall property, kriging analysis was performed to interpolate rainfall data for each grid Thus, these procedures were enable to estimate average rainfall of subbasins. In addition, poor region of rainfall observation was analyzed by spatial interpolation error for each grid and mean error for each subbasin.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.

• Progress in Medical Physics
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• v.8 no.2
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• pp.19-26
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• 1997

3-dimensional Neuronavigator, Viewing Wand(ISG Technologies, Toronto, Cannda) is the surgery aid equipment for real time image (CT or MRI) guided surgery. The assurance of spatial accuracy of this system is important for clinical application. In this study, we have designed the acrylic brain phantom and measured the spatial error with that phantom. The phantom has designed to have capability to simulate image guided surgery. The phantom has 22 vertical rods whose diameters are 5mm and each rods has different length. CT scans were performed by 2.0mm slice and reconstructed for 3-Dimensional analysis. End point of rods can be obtained using reconstructed 3- Dimensional images and they are compared to actual position data. Average deviation was less than 2mm for various situations. Spatial error of Viewing Wand is acceptable in the clinical points of view, while cosmetics of the software needs to be modified to more user friend. Better accuracy can be expected when we apply the mixed fiducial fit registration and surface fit registration method. And even better results can be obtained if registration points distributed even and symetric around the target.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.211-213
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• 2001

히스토그램은 질의 최적화글 위해 사용되는 튿-계 정또 중 하나이다. 최근에는 방대한 데이타에 대한 범위 질의의 선택도 추정 방법의 하나로 사용되기도 한다. 히스토그램을 통한 범위 질의의 선택도 추정 결과는 항상 오차를 포함한다. 따라서 결과의 신뢰성을 보장하기 위해 선택도에 대한 오차를 추정하는 방법이 요구된다. 추정된 선택도의 오차 추정에 대한 기존 방법은 1차원 히스토그램만을 고려하여 하나의 애트리뷰트의 값에 따라 빈도의 분포를 반영하므로 애트리뷰트가 많은 다차원 히스토그램에 바로 적용시키는데 문제가 있다. 이 논문에서는 기존의 추정된 선택도에 대한 오차 추정 기법들을 다차원에 적용할 수 있게 확장한 M-Max, M-Sum 기법을 제안하고, 두 기법을 합친 하이브리드 기법을 제안한다. 실험을 통해 M-Sum 기법과 하이브리드 기법이 M-Max 기법보다 정확한 오차 추정 기법임을 보이고, 또한 작은 기억 공간에서도 두 기법이 오차를 보다 정확하게 추정함을 보인다.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.415-421
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• 2014

In this paper, we proposed problem and improvement of halftoning using random space filling curve. Random space filling curve is developed as a solution for shortcoming which space filling curve has self-similarity. It is used to reduce regular pattern can be occurred in constant brightness area in order that randomness apply to scanning path. But there is a problem that some area along scanning path can show too bright result in halftoning using random space filling curve. In this paper, we analyzed cause of problem and proposed single pixel error diffusion as a solution method. This method can avoid over-accumulated error and show better result in halftoning.