• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.7
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• pp.434-441
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• 2003

This paper proposes a new quantitative and objective image quality metric which is essential to verify the performance of block-based DCT image coding. The proposed metric considers not only global distortion of coded image such as spatial frequency sensitivity and channel masking using HVS based multi-channel model, but also structural distortions caused block-based coding. The experimental results show a strong correlation between proposed metric and subjective metric.

• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.441-446
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• 2013

A split-step time-domain model for the analysis of pulse delay characteristics through ring resonator all-pass filters (APF's) is developed and its accuracy is checked. The dependence of the delay time and pulse distortion on the coupling ratios is investigated using the model. It is observed that the bandwidth of the APF's needs to be wide enough to minimize the pulse distortion.

• ETRI Journal
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• v.33 no.5
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• pp.814-817
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• 2011

In this letter, the distributions of direct current (DC) coefficients for P-frames in H.264/AVC are analyzed, and the distortion model of the Gaussian source under the quantization of the dead-zone plus-uniform threshold quantization with uniform reconstruction quantizer is derived. Experimental results show that the DC coefficients of P-frames are best approximated by the Laplacian distribution and the Gaussian distribution at small quantization step sizes and at large quantization step sizes, respectively.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.7
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• pp.434-434
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• 2003

This paper proposes a new quantitative and objective image quality metric which is essential to verify the performance of block-based DCT image coding The proposed metric considers not only global distortion of coded image such as spatial frequency sensitivity and channel masking using HVS based multi-channel model, but also structural distortions caused block-based coding. The experimental results show a strong correlation between propose(B metric and subjective metric.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.395-402
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• 2010

The seriousness of a traffic accident appears relatively higher on the curve sections compared with the straight sections due to a change in speed caused by a change in the driver's sight. In particular, the visual distortion phenomenon, one of the dangerous factors taking place on the curve sections, appears different according to the road's geometric design. Although it is a genuinely principal design factor which should be necessarily considered in designing a road, the previous researches on establishing the design standards for it have been insufficiently conducted. As a result, the establishment of the road design standards for the curve sections considering the sight distortion phenomenon is desperately required. This research examined the previous researches on the driver's behaviors, the driver's sight characteristics and the perceived curve radius on the curve sections, and developed the theoretical model of perceived curve radius to which a mathematical technique is applied in consideration of the visual distortion phenomenon on the two-lane curve sections in a local area. In addition, after the theoretical visual distortion was calculated on the basis of the theoretical model of perceived curve radius, the range of error on the theoretical recognition radius model formula was verified through comparing it with the previous researches' experiential visual distortion level and analyzing both of them. As a result, it was observed that as the curve radius practically increases in the theoretical recognition curve radius, the range of error tends to go down, which reflects well the characteristics of the curve sections on the road. Based on this research, it is expected that this research will be helpful to eliminate the safety defects when designing the curve sections and contribute to develop the road design standards considering human factors in the future.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.75-80
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• 2002

The mainly used technique to rectify satellite images with distortion is to develop a mathematical relationship between the pixel coordinates on the image and the corresponding points on the ground. By defining the relationship between two coordinate systems, a polynomial model is designed and various linear transformations are used. These GCP based geometric correction has performed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The highly variant height of region is resampled with distortion in the rectified image. To solve this problem this paper proposed the TIN-based rectification on a satellite image. The TIN based rectification is good to correct local distortion, but insufficient to reflect overall structure of one scene. So, this paper shows the experimental result and the analysis of each rectification model. It also describes the relationship GCP distribution and rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1571-1579
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• 2004

Recently, FD(Frame Dropping)-CD(Coefficient Dropping) transcoding is considered mainly due to the low computational complexity and simple implementation. But, CD errors in the FD-CD transtoding scheme tend to be propagated and they have a significant effect on the qualities of decoded images. In this paper, we derive the error characteristics incurred by the CD operations and propose an effective estimation model that adaptively describes well the characteristics of propagation/accumulation errors in compressed domain. Furthermore, we apply the proposed model to distortion control achieving nearly constant distortion allocation among frames. Simulation results show that the proposed model is quite accurate in estimating the overall distortions and is effectively applied to distortion control over a range of sequences with varying scene types.

• Journal of Power Electronics
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• v.18 no.6
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• pp.1889-1900
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• 2018

Harmonic current mitigation is vital in power distribution networks owing to the inflow of nonlinear loads, distributed generation, and renewable energy sources. The active power filter (APF) is the current electrical equipment that can dynamically compensate for harmonic distortion and eliminate asymmetrical loads. The compensation performance of an APF largely depends on the control strategy applied to the voltage source inverter (VSI). Model predictive control (MPC) has been demonstrated to be one of the effective control approaches to providing fast dynamic responses. This approach covers different types of power converters due to its several advantages, such as flexible control scheme and simple inclusion of nonlinearities and constraints within the controller design. In this study, a finite control set-MPC technique is proposed for the control of VSIs. Unlike conventional control methods, the proposed technique uses a discrete time model of the shunt APF to predict the future behavior of harmonic currents and determine the cost function so as to optimize current errors through the selection of appropriate switching states. The viability of this strategy in terms of harmonic mitigation is verified in MATLAB/Simulink. Experimental results show that MPC performs well in terms of reduced total harmonic distortion and is effective in APFs.

• Atmosphere
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• v.17 no.4
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• pp.381-391
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• 2007

The characteristics of flow around a single obstacle with fixed height and varied length and width are numerically investigated using a computational fluid dynamics (CFD) model. As the obstacle length increases, flow distortion near the upwind side of the obstacle increases and the size of the recirculation zone behind the obstacle also increases. As the obstacle width increases, the size of the recirculation zone decreases, despite almost invariable flow distortion near the upwind side of the obstacle. Flow passing through an obstacle is separated, one part going around the obstacle and the other crossing over the obstacle. The size of the recirculation zone is determined by the distance between the obstacle and the point (reattachment point) at which both the flows converge. When the obstacle width is relatively large, flows are reattached at the obstacle surface and their recoveries occur. Resultant shortening of the paths of flows crossing over and going around decreases the size of the recirculation zone. To support this, the extent of flow distortion defined based on the change in wind direction is analyzed. The result shows that flow distortion is largest near the ground surface and decreases with height. An increase in obstacle length increases the frontal area fraction of flow distortion around the obstacle. In the cases of increasing the width, the frontal area fraction near the upwind side of the obstacle does not change much, but near the downwind side, it becomes larger as the width increases. The frontal area fraction is in a better correlation with the size of the recirculation zone than the building aspect ratios, suggesting that the frontal area fraction is a good indicator for explaining the variation in the size of the recirculation zone with the building aspect ratios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.288-307
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• 2016

Image distortions are typically characterized by degradations of structures. Dictionaries learned from natural images can capture the underlying structures in images, which are important for image quality assessment (IQA). This paper presents a general-purpose no-reference image quality metric using a GRadient-Induced Dictionary (GRID). A dictionary is first constructed based on gradients of natural images using K-means clustering. Then image features are extracted using the dictionary based on Euclidean-norm coding and max-pooling. A distortion classification model and several distortion-specific quality regression models are trained using the support vector machine (SVM) by combining image features with distortion types and subjective scores, respectively. To evaluate the quality of a test image, the distortion classification model is used to determine the probabilities that the image belongs to different kinds of distortions, while the regression models are used to predict the corresponding distortion-specific quality scores. Finally, an overall quality score is computed as the probability-weighted distortion-specific quality scores. The proposed metric can evaluate image quality accurately and efficiently using a small dictionary. The performance of the proposed method is verified on public image quality databases. Experimental results demonstrate that the proposed metric can generate quality scores highly consistent with human perception, and it outperforms the state-of-the-arts.