• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.474-483
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• 2018

In this paper, we propose a multi-scale high dynamic range (HDR) tone mapping algorithm using guided image filter (GIF). The GIF is used to divide an image into a base layer and a detail layer, then the range of the detail layer is reduced with a compression function to enhance the detail information of the image. However, in most cases, an image includes the detail and edge information in different scales. That is to say, it is difficult to represent all detail features under a certain scale, and a single-scale image decomposition method is not free from artifacts around edges. To solve the problems, the multi-scale image decomposition method is proposed. It utilizes the detail layers of several scale to determine how much edge is preserved. Experiment results show that the proposed algorithm has better image performance in preserving edge compared to conventional algorithm.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.6
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• pp.1365-1373
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• 1994

Elasto-dynamic deformation of flexible linkage mechanism was analyzed using the finite element method. A computer program was constructed and applied to analyze a specific crank-level 4-bar mechanism, in which the elasto-dynamic deformation of the mechanism system was obtained using mode superposition method in the case of constant input speed and the effect of geometric stiffness on the mechanism is included. Experimental verification of numerical results was conducted by measuring the elasto-dynamic deformation of mid-points of coupler and lever for the 4-bar lingkage mechanism using high speed camera and image data processing systeem. For the elasto-dynamic deformation at the lever mid-point, the numerical results including geometric stiffness almost agree with the experimental ones. However, the numerical results excluding geometric stiffness good agree with the experimental ones at the couper mid-point.

• 한국가시화정보학회:학술대회논문집
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• 2004.12a
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• pp.41-45
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• 2004

The dynamic particle image velocimetry (PIV) is consisted of a high frequency pulse laser, high speed cameras and a timing controller. The three velocity components of flow downstream of an axial flow fan for PC cooling system are measured using the dynamic PIV system. An Axial flow fan has seven blades of 72 mm in diameter. The rotating speed is 1800 rpm. The downstream flow is visualized by smoke particles of about $0.3-1\;{\mu}m$ in diameter. The three-dimensional instantaneous velocity fields are measured at three downstream planes. The swirl velocity component was diffused downstream and the change in time-mean vorticity distribution downstream was also discussed. The spatio-temporal change in axial velocity component with the blades passing is recognized by the instantaneous vector maps. And the dynamic behavior of vorticity moving with the rotating blades is discussed using the unsteady vorticity maps.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.46-53
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• 2010

Purpose: The static image of nuclear medicine study should be acquired without a motion, however, it is difficult to acquire static image without movement for the serious patients, advanced aged patients. These movements cause decreases in reliability for quantitative and qualitative analysis, therefore re-examination was inevitable in the some cases. Consequently, in order to improve the problem of motion artifacts, the authors substituted the dynamic acquisition technique for the static acquisition, using motion correction. Materials and Methods: A capillary tube and IEC body phantom were used. First, the static image was acquired for 60 seconds while the dynamic images were acquired with a protocol, 2 sec/frame${\times}$30 frames, under the same parameter and the frames were summed up into one image afterwards. Also, minimal motion and excessive motion were applied during the another dynamic acquisition and the coordinate correction was applied towards X and Y axis on the frames where the motion artifact occurred. But the severe blurred images were deleted. Finally, the resolution and counts were compared between the static image and the summed dynamic images which before and after applying motion correction, and the signal of frequency was analysed after frequency spatial domain was transformed into 2D FFT. Supplementary examination, the blind test was performed by the nuclear medicine department staff. Results: First, the resolution in the static image and summed dynamic image without motion were 8.32 mm, 8.37 mm on X-axis and 8.30 mm, 8.42 mm on Y-axis, respectively. The counts were 484 kcounts, 485 kcounts each, so there was nearly no difference. Secondly, the resolution in the image with minimal motion applying motion correction was 8.66 mm on X-axis, 8.85 mm on Y-axis and had 469 kcounts while the image without motion correction was 21.81 mm, 24.02 mm and 469 kcounts in order. So, this shows the image with minimal motion applying motion correction has similar resolution with the static image. Lastly, the resolution in the images with excessive motion applying motion correction were 9.09 mm on X-axis, 8.83 mm on Y-axis and had 469 kcounts while the image without motion correction was 47.35 mm, 40.46 mm and 255 kcounts in order. Although there was difference in counts because of deletion of blurred frames, we could get similar resolution. And when the image was transformed into frequency, the high frequency was decreased by the movement. However, the frequency was improved again after motion correction. In the blind test, there was no difference between the image applying motion correction and the static image without motion. Conclusion: There was no significant difference between the static image and the summed dynamic image. This technique can be applied to patients who may have difficulty remaining still during the imaging process, so that the quality of image can be improved as well as the reliance for analysis of quantity. Moreover, the re-examination rate will be considerably decreased. However, there is a limit of motion correction, more time will be required to successfully image the patients applying motion correction. Also, the decrease of total counts due to deletion of the severe blurred images should be calculated and the proper number of frames should be acquired.

• Journal of the Korea Computer Graphics Society
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• v.18 no.2
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• pp.1-8
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• 2012

High dynamic range (HDR) images represent a far wider numerical range of exposures than common digital images. Thus it can accurately store intensity levels of light found in the specific scenes generated by light sources in the real world. Although a kind of professional HDR cameras which support fast accurate capturing has been developed, high costs prevent from employing those in general working environments. The common method to produce a HDR image with lower cost is to take a set of photos of the target scene with a range of exposures by general purpose cameras, and then to transform them into a HDR image by commercial softwares. However, the method needs complicate and accurate camera calibration processes. Furthermore, creating HDR environment maps which are used to produce high quality imaging contents includes delicate time-consuming manual processes. In this paper, we present an automatic HDR panorama environment map generating system which was constructed to make the complicated jobs of taking pictures easier. And we show that our system can be effectively applicable to photo-realistic compositing tasks which combine 3D graphic models with a 2D background scene using image-based lighting techniques.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.267-268
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• 2007

A dynamic range compression algorithm using Markov random field (MRF) modeling to display high dynamic range (HDR) images on low dynamic range (LDR) devices is proposed in this work. The proposed algorithm separates foreground objects from the background using the edge information, and then compresses the color differences across the edges based on the MRF modeling. By minimizing a cost function using belief propagation, the proposed algorithm can provide an effective LDR image. Simulation results show that the proposed algorithm provides good results.

• Journal of the Korean Society of Radiology
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• v.10 no.4
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• pp.247-253
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• 2016

Ultrasound devices diagnose many disease, which is widely used, can not be standardized quantitative evaluated in order to evaluate sonography image of quality. Therefore, in this papers, aims to get correct image in order to accurate diagnosis by figuring out the appropriate parameter based on each target by measuring distortion which results in the analyzation of the sensitivity of SNR and the histogram of signal by manipulating parameter of 8 mm target in ATS-539 multipurpose phantom. Equipment using Acuson sequoia 512, convex probe and utilizes multi-objective phantom. experiment method is that first you put the phantom on the flat and acquire 85 sheets of image, changing frequency(2,3,4 MHz, harmonic 3, 4, 4.5 MHz), Focus(2, 4, 6 unit), and Dynamic Range(58, 68, 78, 88, 98) for a 8 mm structure. through the Image J program. The sensitivity angle of 8mm target through Image J program is gauged by each separate target SNR and the distorted angle subtract and measure Histogram of background from Histogram of signal and take top 40% from the given result value above. According to parameter variation we found out proper parameter by acquiring SNR of sensitivity and distortion data for aspect of transition. The more this findings have Focus, the lower distortion value and at 4 MHz frequency this result have high SNR and low distortion value. Dynamic Range got an appropriate image on 88 and 98. It is considered on the basis of the experimental data, the probability of disease diagnosis will get higher.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1846-1863
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• 2016

High dynamic range (HDR) images can present the perfect real scene and rich color information. A commonly encountered problem in practical applications is how to well visualize HDR images on standard display devices. In this paper, we propose a multi-scale decomposition method using guided filtering for HDR image tone mapping. In our algorithm, HDR images are directly decomposed into three layers：base layer, coarse scale detail layer and fine detail layer. We propose an effective function to compress the base layer and the coarse scale detail layer. An adaptive function is also proposed for detail adjustment. Experimental results show that the proposed algorithm effectively accomplishes dynamic range compression and maintains good global contrast as well as local contrast. It also presents more image details and keeps high color saturation.

• Journal of the Semiconductor & Display Technology
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• v.15 no.4
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• pp.103-106
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• 2016

3D technology is main factor in Augmented Reality. Depth map is essential to make cubic effect using 2d image. There are a lot of ways to construct Depth map. Among them, stereo matching is mainly used. This paper presents how to generate depth map using stereo matching. For stereo matching, existing Dynamic programming method is used. To make accurate stereo matching, High-Boost Filter is applied to preprocessing method. As a result, when depth map is generated, accuracy based on Ground Truth soared.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.203-206
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• 2007

The Space-borne electro-optical camera system has panchromatic redundant image channel as well as primary channel in order to increase reliability of satellite system. In most case redundant channel never been used during the whole mission period. Staggered array configuration using redundant image channel and new operation mode proposed which operates primary and redundant channel simultaneously. Without new hardware design, fast electronics and system complexity, we can get 1.414 times more fine GSD image of original system or we can get 1.414 times more SNR or High dynamic range imaging mode. In this paper we deal with several image quality improvement methods using dual panchromatic channel.