• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.626-632
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• 2016

In this paper, we propose the defect emphasis in TFT-LCD panel image. The defect emphasis image consist of S(Shape) map and B(Brightness) map. S map based on DoG(difference of gaussian) is made with the mura defect shape characteristic. And B map use defect intensity property that defect intensity is higher than background. The experiments were conducted to evaluate the performance of the proposed defect emphasis method. The results of experiments show the validity of the defect emphasis using the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2927-2936
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• 2013

In this paper, we propose a noise reduction and hole removal algorithm in order to improve the quality of depth images when they are used for creating 3D contents. In the proposed algorithm, the depth image and the corresponding color image are both used. First, an intensity image is generated by converting the RGB color space into the HSI color space. By estimating the difference of distance and depth between reference and neighbor pixels from the depth image and difference of intensity values from the color image, they are used to remove noise in the proposed algorithm. Then, the proposed hole filling method fills the detected holes with the difference of euclidean distance and intensity values between reference and neighbor pixels from the color image. Finally, we apply a parallel structure of GPGPU to the proposed algorithm to speed-up its processing time for real-time applications. The experimental results show that the proposed algorithm performs better than other conventional algorithms. Especially, the proposed algorithm is more effective in reducing edge blurring effect and removing noise and holes.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.101-110
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• 2006

The accuracy of rural land cover using airborne multispectral images and LEAR (Light Detection And Ranging) data was analyzed. Multispectral image consists of three bands in green, red and near infrared. Intensity image was derived from the first returns of LIDAR, and vegetation height image was calculated by difference between elevation of the first returns and DEM (Digital Elevation Model) derived from the last returns of LIDAR. Using maximum likelihood classification method, three bands of multispectral images, LIDAR vegetation height image, and intensity image were employed for land cover classification. Overall accuracy of classification using all the five images was improved to 85.6% about 10% higher than that using only the three bands of multispectral images. The classification accuracy of rural land cover map using multispectral images and LIDAR images, was improved with clear difference between heights of different crops and between heights of crop and tree by LIDAR data and use of LIDAR intensity for land cover classification.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.462-470
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• 2020

Objective: To demonstrate that human visual illusion can contribute to sub-endocardial dark rim artifact in contrast-enhanced myocardial perfusion magnetic resonance images. Materials and Methods: Numerical phantoms were generated to simulate the first-passage of contrast agent in the heart, and rendered in conventional gray scale as well as in color scale with reduced luminance variation. Cardiac perfusion images were acquired from two healthy volunteers, and were displayed by the same gray and color scales used in the numerical study. Before and after k-space windowing, the left ventricle (LV)-myocardium boarders were analyzed visually and quantitatively through intensity profiles perpendicular the boarders. Results: k-space windowing yielded monotonically decreasing signal intensity near the LV-myocardium boarder in the phantom images, as confirmed by negative finite difference values near the board ranging -1.07 to -0.14. However, the dark band still appears, which is perceived by visual illusion. Dark rim is perceived in the in-vivo images after k-space windowing that removed the quantitative signal dip, suggesting that the perceived dark rim is a visual illusion. The perceived dark rim is stronger at peak LV enhancement than the peak myocardial enhancement, due to the larger intensity difference between LV and myocardium. In both numerical phantom and in-vivo images, the illusory dark band is not visible in the color map due to reduced luminance variation. Conclusion: Visual illusion is another potential cause of dark rim artifact in contrast-enhanced myocardial perfusion MRI as demonstrated by illusory rim perceived in the absence of quantitative intensity undershoot.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.239-247
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• 2012

This paper is related to an Object VR-based virtual textile wearing system carrying out textile texture mapping based on viewpoint vector estimation and intensity difference map. The proposed system is characterized as capable of virtually wearing a new textile pattern selected by the user to the clothing shape section segmented from multi-view 2D images of clothes model for Object VR(Object Virtual Reality), and three-dimensionally viewing its virtual wearing appearance at multi-view points of the object. Regardless of color or intensity of model clothes, the proposed system is possible to virtually change the textile pattern with holding the properties of the selected clothing shape section, and also to quickly and easily simulate, compare, and select multiple textile pattern combinations for individual styles or entire outfits. The proposed system can provide higher practicality and easy-to-use interface, as it makes real-time processing possible in various digital environment, and creates comparatively natural and realistic virtual wearing styles, and also makes semi-automatic processing possible to reduce the manual works.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1677-1684
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• 1996

The theory of optimal stack filtering has been used in difference of estimates(DoE) approach to the detection of intensity edges in noisy image. In this approach, stack filters are applied to a noisy image to obtain local estimates of the dilated and eroded versions of the noise-free image. Thresholding the difference between these two estimates produces the estimated edge map. In this paper, the DoE approach is modified by imposing a symmetry condition of the data used to train the two stack filers. Under this condition, the stack filters obtained are duals of each other. Only one filter must therefore be trained;the other is simply its dual. They also produce statistially unbiased estimates. This new technique is called the symmetric Difference of Estimates (SDoE) approach.

• Investigative Magnetic Resonance Imaging
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• v.19 no.2
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• pp.107-113
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• 2015

Purpose: Susceptibility weighted imaging (SWI) is a new magnetic resonance technique that can exploit the magnetic susceptibility differences of various tissues. Intracranial hemorrhage (ICH) looks a dark blooming on the magnitude images of SWI. However, the pattern of ICH on phase images is not well known. The purpose of this study is to characterize hemorrhagic lesions on the phase images of SWI. Materials and Methods: We retrospectively enrolled patients with ICH, who underwent both SWI and precontrast CT, between 2012 and 2013 (n = 95). An SWI was taken, using the 3-tesla system. A phase map was generated after postprocessing. Cases with an intracranial hemorrhage were reviewed by an experienced neuroradiologist and a trainee radiologist, with 10 years and 3 years of experience, respectively. The types and stages of the hemorrhages were determined in correlation with the precontrast CT, the T1- and T2-weighted images, and the FLAIR images. The size of the hemorrhage was measured by a one- directional axis on a magnitude image of SWI. The phase values of the ICH were qualitatively evaluated: hypo-, iso-, and hyper-intensity. We summarized the imaging features of the intracranial hemorrhage on the phase map of the SWI. Results: Four types of hemorrhage are observed: subdural and epidural; subarachnoid; parenchymal hemorrhage; and microbleed. The stages of the ICH were classified into 4 groups: acute (n = 34); early subacute (n = 11); late subacute (n = 15); chronic (n = 8); stage-unknown microbleeds (n = 27). The acute and early subacute hemorrhage showed heterogeneous mixed hyper-, iso-, and hypo-signal intensity; the late subacute hemorrhage showed homogeneous hyper-intensity, and the chronic hemorrhage showed a shrunken iso-signal intensity with the hyper-signal rim. All acute subarachnoid hemorrhages showed a homogeneous hyper-signal intensity. All parenchymal hemorrhages (> 3 mm) showed a dipole artifact on the phase images; however, microbleeds of less than 3 mm showed no dipole artifact. Larger hematomas showed a heterogeneous mixture of hyper-, iso-, and hypo-signal intensities. Conclusion: The pattern of the phase value of the SWI showed difference, according to the type, stage, and size.

• Journal of Environmental Science International
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• v.30 no.12
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• pp.1101-1111
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• 2021

In this study, among the W-S-R(Wiper-Signal-Rainfall) relationship methods used to produce sensor-based rain information in real time, we sought to produce actual rainfall information by applying machine learning techniques to account for the effects of wiper operation. To this end, we used the gradient descent and threshold map methods for pre-processing the cumulative value of the difference before and after wiper operation by utilizing four sensitive channels for optical sensors which collected rain sensor data produced by five rain conditions in indoor artificial rainfall experiments. These methods produced rainfall information by calculating the average value of the threshold according to the rainfall conditions and channels, creating a threshold map corresponding to the 4 (channel) × 5 (considering rainfall information) grid and applying Optima Rainfall Intensity among the big data processing techniques. To verify these proposed results, the application was evaluated by comparing rainfall observations.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.52-63
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• 2021

In previous research, the coastal wetlands were detected by using the vegetation indices or land cover classification maps derived from the multispectral bands of the satellite or aerial imagery, and this approach caused the various limitations for detecting the coastal wetlands with high accuracy due to the difficulty of acquiring both land cover and topographic information by using the single remote sensing data. This research suggested the efficient methodology for detecting the coastal wetlands using the sentinel-2 satellite image and SRTM(Shuttle Radar Topography Mission) DEM (Digital Elevation Model) acquired in Gomsoman Bay, west coasts of South Korea through the following steps. First, the NDWI(Normalized Difference Water Index) image was generated using the green and near-infrared bands of the given Sentinel-2 satellite image. Then, the binary image that separating lands and waters was generated from the NDWI image based on the pixel intensity value 0.2 as the threshold and the other binary image that separating the upper sea level areas and the under sea level areas was generated from the SRTM DEM based on the pixel intensity value 0 as the threshold. Finally, the coastal wetland map was generated by overlaying analysis of these binary images. The generated coastal wetland map had the 94% overall accuracy. In addition, the other types of wetlands such as inland wetlands or mountain wetlands were not detected in the generated coastal wetland map, which means that the generated coastal wetland map can be used for the coastal wetland management tasks.

• Journal of Yeungnam Medical Science
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• v.37 no.2
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• pp.90-97
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• 2020

Background: To minimize damage to the ovarian reserve, it is necessary to evaluate the follicular density in the ovarian tissue surrounding endometriosis on preoperative imaging. The purpose of the present study was to evaluate the usefulness of subtraction pelvic magnetic resonance imaging (MRI) to detect ovarian reserve. Methods: A subtracted T1-weighted image (^subT1WI) was obtained by subtracting unenhanced T1WI from contrast-enhanced T1WI (^ceT1WI) with similar parameters in 22 patients with ovarian endometriosis. The signal-to-noise ratio (SNR) in ovarian endometriosis, which was classified into the high signal intensity and iso-to-low signal intensity groups on the T2-weighted image, was compared to that in normal ovarian tissue. To evaluate the effect of contrast enhancement, a standardization map was obtained by dividing ^subT1WI by ^ceT1WI. Results: On visual assessment of 22 patients with ovarian endometriosis, 16 patients showed a high signal intensity, and 6 patients showed an iso-to-low signal intensity on T1WI. Although SNR in endometriosis with a high signal intensity was higher than that with an iso-to-low signal intensity, there was no difference in SNR after the subtraction (13.72±77.55 vs. 63.03±43.90, p=0.126). The area of the affected ovary was smaller than that of the normal ovary (121.10±22.48 vs. 380.51±75.87 ㎟, p=0.002), but the mean number of pixels in the viable remaining tissue of the affected ovary was similar to that of the normal ovary (0.53±0.09 vs. 0.47±0.09, p=0.682). Conclusion: The subtraction technique used with pelvic MRI could reveal the extent of endometrial invasion of the normal ovarian tissue and viable remnant ovarian tissue.