• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3092-3107
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• 2019

Visible-infrared image fusion is a process of synthesizing an infrared image and a visible image into a fused image. This process synthesizes the complementary advantages of both images. The infrared image is able to capture a target object in dark or foggy environments. However, the utility of the infrared image is hindered by the blurry appearance of objects. On the other hand, the visible image clearly shows an object under normal lighting conditions, but it is not ideal in dark or foggy environments. In this paper, we propose a multi-guided filter and a real-time image fusion method. The proposed multi-guided filter is a modification of the guided filter for multiple guidance images. Using this filter, we propose a real-time image fusion method. The speed of the proposed fusion method is much faster than that of conventional image fusion methods. In an experiment, we compare the proposed method and the conventional methods in terms of quantity, quality, fusing speed, and flickering artifacts. The proposed method synthesizes 57.93 frames per second for an image size of $320{\times}270$. Based on our experiments, we confirmed that the proposed method is able to perform real-time processing. In addition, the proposed method synthesizes flicker-free video.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.509-520
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• 2005

Data fusion is defined as the process of combining data and information from different sources for the effectiveness of the usage of useful information contents. In this paper, we propose a data fusion algorithm using k-means clustering method for data enrichment to improve data quality in knowledge discovery in database(KDD) process. An empirical study was conducted to compare the proposed data fusion technique with the existing techniques and shows that the newly proposed clustering data fusion technique has low MSE in continuous fusion variables.

• 한국데이터정보과학회:학술대회논문집
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• 2005.10a
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• pp.35-45
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• 2005

Data fusion is method to combination data. The purpose of this study is to design and implementation for street fashion information analysis system using data fusion. It can offer variety and actually information because it can fuse image data and survey data for street fashion. Data fusion method exists exact matching method, judgemental matching method, probability matching method, statistical matching method, data linking method, etc. In this study, we use exact matching method. Our system can be visual information analysis of customer's viewpoint because it can analyze both each data and fused data for image data and survey data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.724-726
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• 2003

Currently available image fusion methods are not efficient for fusing the Landsat 7 images. Significant color distortion is one of the major problems. In this paper, using the well-known wavelet based method for data fusion between high-resolution panchromatic and low-resolution multispectral satellite images, we performed Landsat 7 image fusion. Based on the experimental results obtained from this study, we analyzed some reasons for color distortion. A new approach using the biorthogonal wavelets based method for data fusion is presented. This new method has reached an optimum fusion result - with the same spectral resolution as the multispectral image and the same spatial resolution as the panchromatic image with minimum artifacts.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1386-1394
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• 2016

Pyramid fusion usually adjusts the Laplacian weights of pixels of the input images by evaluating predefined criteria. This has advantages that it can selectively express intense color and enhance the contrast when applied to HDR exposure fusion. But it may cause noise because the weights are determined by pixel importance without considering the interdependent pixel relationship that constitutes a scene. This paper proposes a fusion method using simple weight criteria generated from the gray pixel values, which is expected to preserve the interdependent relationship and improve execution speed. In order to evaluate the performance of the proposed method we examine a homogeneity measure, H and compare the execution time for both methods. The proposed method is found to be more advantageous with respect to homogeneity and execution speed.

• Journal of Korean Society for Quality Management
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• v.49 no.1
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• pp.1-15
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• 2021

Purpose: The purpose of this study was to propose a sensor fusion algorithm that integrates vehicle motion sensor(VMS) into the hybrid navigation system. Methods: How to evaluate the navigation performance was comparison test with the hybrid navigation system and the sensor fusion method. Results: The results of this study are as follows. It was found that the effects of the sensor fusion method and α value estimation were significant. Applying these greatly improves the navigation performance. Conclusion: For improving the reliability of navigation system, the sensor fusion method shows that the proposed method improves the navigation performance in a combat vehicle.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.8
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• pp.652-660
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• 2003

T-history method, measuring heat-of-fusion of phase change material (PCM) in sealed tubes, has the advantages of a simple experimental device and no requirements in sampling process. However, a degree of supercooling used in selecting the range of latent heat release and neglecting sensible heat during the phase change process can cause significant errors in determining the heat of fusion in the original method, which has been improved in order to predict better results by us. In the present study, the modified method was applied to a variety of PCM such as paraffin and lauric acid having very small or no supercooling with a satisfactory precision. Also the selection of inflection point and temperature measurement position was fumed out not to affect the accuracy of heat-of-fusion significantly. As a result, the method can provide an appropriate means to assess a new developed PCM by cycle test even if a very accurate value cannot be obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.5-24
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• 2010

Data fusion is an attractive technology because it allows various trade-offs related to performance metrics, e.g., energy, latency, accuracy, fault-tolerance and security in wireless sensor networks (WSNs). Under a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets, so that the complexity for the fusion process is increased due to the existence of various physical attributes. In this paper, we first investigate the process and performance of multi-attribute fusion in data gathering of WSNs, and then propose a self-adaptive threshold method to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Based on our proposed methods, we design a novel energy equilibrium routing method for WSNs, viz., multi-attribute fusion tree (MAFT). Simulation results demonstrate that MAFT achieves very good performance in terms of the network lifetime.

• Structural Engineering and Mechanics
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• v.31 no.3
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• pp.333-347
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• 2009

Due to structural complicacy, structural health monitoring for civil engineering needs more accurate and effectual methods of damage identification. This study aims to import multi-source information fusion (MSIF) into structural damage diagnosis to improve the validity of damage detection. Firstly, the essential theory and applied mathematic methods of MSIF are introduced. And then, the structural damage identification method based on multi-mode information fusion is put forward. Later, on the basis of a numerical simulation of a concrete continuous box beam bridge, it is obviously indicated that the improved modal strain energy method based on multi-mode information fusion has nicer sensitivity to structural initial damage and favorable robusticity to noise. Compared with the classical modal strain energy method, this damage identification method needs much less modal information to detect structural initial damage. When the noise intensity is less than or equal to 10%, this method can identify structural initial damage well and truly. In a word, this structural damage identification method based on multi-mode information fusion has better effects of structural damage identification and good practicability to actual structures.

• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.410-419
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• 2004

In this paper. we propose a method of confidence measure fusion under Bayesian framework for speech recognition. Centralized and distributed schemes are considered for confidence measure fusion. Centralized fusion is feature level fusion which combines the values of individual confidence scores and makes a final decision. In contrast. distributed fusion is decision level fusion which combines the individual decision makings made by each individual confidence measuring method. Optimal Bayesian fusion rules for centralized and distributed cases are presented. In isolated word Out-of-Vocabulary (OOV) rejection experiments. centralized Bayesian fusion shows over 13% relative equal error rate (EER) reduction compared with the individual confidence measure methods. In contrast. the distributed Bayesian fusion shows no significant performance increase.