• Journal of Korea Multimedia Society
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• v.8 no.2
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• pp.249-257
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• 2005

This paper aims at reducing aliasing in pixel-based rendering for 3D implicit surfaces by shifted multi Z-buffers. The voxelized implicit surfaces with high resolution take so much time in generating high Quality image without aliasing. So in rendering a voxelized implicit surfaces, a new antialiasing method which can generate a high quality image at a lower resolution is required. Therefore, this paper suggests that a method which get various sampling values by shifting several z-buffers in each voxel and average them, The advantages are effective memory, simple calculation and easy convergence with various filters. But, the increase of number of z-buffer also increase the consuming time rapidly. Therefore, the research for representing the relation the degree of image quality with the consumption of time as a number is required.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.171-178
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• 2004

The advantage of the remote sensing is extraction the information of wide area rapidly. Such advantage is the resource and environment are quick and efficient method to grasps accurately method through the land cover classification of wide area. Accordingly this study was presented more better land cover classification method through an algorithm development. We accomplished FCM(Fuzzy C-Mean) classification technique with MLC (Maximum Likelihood classification) technique to be general land cover classification method in the content of research. And evaluated the accuracy assessment of two classification method. This study is used to the high-resolution(6.6m) Electro-Optical Camera(EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1(KOMPSAT-1) and the multi-spectral Moderate Resolution Imaging Spectroradiometer(MODIS) image data(36 bands).

• Journal of radiological science and technology
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• v.42 no.1
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• pp.39-46
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• 2019

This study conducted a comparative analysis of differences between cartesian trajectory in a linear rectangular coordinate system and MultiVane trajectory in a nonlinear rectangular coordinate system axial T1 and axial T2 images using an American College of Radiology(ACR) phantom. The phantom was placed at the center of the head coil and the top-to-bottom and left-to-right levels were adjusted by using a level. The experiment was performed according to the Phantom Test Guidance provided by the ACR, and sagittal localizer images were obtained. As shown in Figure 2, slices # 1 and # 11 were scanned after placing them at the center of a $45^{\circ}$ wedge shape, and a total of 11 slices were obtained. According to the evaluation results, the image intensity uniformity(IIU) was 93.34% for the cartesian trajectory, and 93.19% for the MultiVane trajectory, both of which fall under the normal range in the axial T1 image. The IIU for the cartesian trajectory was 0.15% higher than that for the MultiVane trajectory. In axial T2, the IIU was 96.44% for the cartesian trajectory, and 95.97% for the MultiVane trajectory, which fall under the normal range. The IIU for the cartesian trajectory was by 0.47% higher than that for the MultiVane trajectory. As a result, the cartesian technique was superior to the MultiVane technique in terms of the high-contrast spatial resolution, image intensity uniformity, and low-contrast object detectability.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.27-33
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• 2022

In this paper, we propose a novel generator architecture for multi-domain style transfer method not an image to image translation, as a method of generating a styled image by transfering a style to the content image. A latent vector and Gaussian noises are added to the generator of GAN so that a high quality image is generated while considering the characteristics of various data distributions for each domain and preserving the features of the content data. With the generator architecture of the proposed GAN, networks are configured and presented so that the content image can learn the styles for each domain well, and it is applied to the domain composed of images of the four seasons to show the high resolution style transfer results.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1436-1439
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• 2002

In this paper, based on the data link model characterized by the spaceborne small SAR system, the high rate multi-channel data link module is designed including link storage, link processor, transmitter, and wide-angle antenna. The design results are presented with the performance analysis on the data link budget as well as the multi-mode data rate in association with the SAR imaging mode of operation from high resolution to the wide swath.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.47-54
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• 2012

Additional high resolution satellite images, other period or site, are essential for efficient city modeling and analysis. However, the same ground objects have a radiometric inconsistency in different satellite images and it debase the quality of image processing and analysis. Moreover, in an urban area, buildings, trees, bridges, and other artificial objects cause shadow effects, which lower the performance of relative radiometric normalization. Therefore, in this study, we exclude shadow areas and suggest the selective histogram matching methods for image based application without supplementary digital elevation model or geometric informations of sun and sensor. We extract the shadow objects first using adjacency informations with the building edge buffer and spatial and spectral attributes derived from the image segmentation. And, Outlier objects like a asphalt roads are removed. Finally, selective histogram matching is performed from the shadow masked multi-temporal Quickbird-2 images.

• Journal of The Korean Astronomical Society
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• v.47 no.2
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• pp.43-47
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• 2014

Many advanced ground-based solar telescopes improve the spatial resolution of observation images using an adaptive optics (AO) system. As any AO correction remains only partial, it is necessary to use post-processing image reconstruction techniques such as speckle masking or shift-and-add (SAA) to reconstruct a high-spatial-resolution image from atmospherically degraded solar images. In the New Vacuum Solar Telescope (NVST), the spatial resolution in solar images is improved by frame selection and SAA. In order to overcome the burden of massive speckle data processing, we investigate the possibility of using the speckle reconstruction program in a real-time application at the telescope site. The code has been written in the C programming language and optimized for parallel processing in a multi-processor environment. We analyze the scalability of the code to identify possible bottlenecks, and we conclude that the presented code is capable of being run in real-time reconstruction applications at NVST and future large aperture solar telescopes if care is taken that the multi-processor environment has low latencies between the computation nodes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.3
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• pp.664-668
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• 2010

This paper presents a System-On-a-chip (SoC) for embedded image processing and pattern recognition applications that need Gaussian Pyramid structure. The system is fully implemented into Field-Programmable Gate Array (FPGA) based on the prototyping platform. The SoC consists of embedded processor core and a hardware accelerator for Gaussian Pyramid construction. The performance of the implementation is benchmarked against software implementations on different platforms.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1154-1158
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• 2016

This paper presents a System-On-a-chip for embedded image processing applications that need Gaussian Pyramid structure. The system is fully implemented into Field-Programmable Gate Array (FPGA) based on the prototyping platform. The SoC consists of embedded processor core and a hardware accelerator for Gaussian Pyramid construction. The performance of the implementation is benchmarked against software implementations on different platforms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.246-253
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• 2016

Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.