• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.1-5
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• 2021

Although CT has an advantage in describing the three-dimensional anatomical structure of the human body, it also has a disadvantage in that high doses are exposed to the patient. Recently, a deep learning-based image reconstruction method has been used to reduce patient dose. The purpose of this study is to analyze the dose reduction and image quality improvement of deep learning-based reconstruction (DLR) on the adult's chest CT examination. Adult lung phantom was used for image acquisition and analysis. Lung phantom was scanned at ultra-low-dose (ULD), low-dose (LD), and standard dose (SD) modes, and images were reconstructed using FBP (Filtered back projection), IR (Iterative reconstruction), DLR (Deep learning reconstruction) algorithms. Image quality variations with respect to varying imaging doses were evaluated using noise and SNR. At ULD mode, the noise of the DLR image was reduced by 62.42% compared to the FBP image, and at SD mode, the SNR of the DLR image was increased by 159.60% compared to the SNR of the FBP image. Based on this study, it is anticipated that the DLR will not only substantially reduce the chest CT dose but also drastic improvement of the image quality.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.2
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• pp.181-192
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• 2002

The purpose of this study is to clarify the expression of conceptual image by which the modern graphic artists use for creating new visual images and the characteristics in expression of the major fashion images in fashion illustration. In the present study, major findings on the basis of the analysis of expression of visual images in fashion illustration since 1980s are as follow: The conceptual image expression in the visual arts is based on the eight techniques. They are dual image, operation of image, copying·reproduction of image, deconstruction of image, pictorial image, symbolization of image, mystification of image, and making humorous image. Since 1980s, the major fashion images in fashion illustration are mainly classified as classic image, humor image, fantastic image, natural image, avant-garde image, simple image, casual image and feminine image. The characteristics in expression of these images in fashion illustration are; 1) fortification of dual image in classic image, 2) activation in humor image 3) grotesque fantastic image, 4) the modernization of natural image, etc. In addition that, the image of avant-garde is expressed by Postermodernism, Deconstructionism, Techno etc. since 1980s. Also, simple image of the modern composition, casual image of daily life, and feminine image which is emphasized with eroticism are also included in these characteristic in expression of images since 1980s.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2748-2766
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• 2016

Compared with traditional patch-based sparse representation, recent studies have concluded that group-based sparse representation (GSR) can simultaneously enforce the intrinsic local sparsity and nonlocal self-similarity of images within a unified framework. This article investigates an accelerated split Bregman method (SBM) that is based on GSR which exploits image compressive sensing (CS). The computational efficiency of accelerated SBM for the measurement matrix of a partial Fourier matrix can be further improved by the introduction of a fast Fourier transform (FFT) to derive the enhanced algorithm. In addition, we provide convergence analysis for the proposed method. Experimental results demonstrate that accelerated SBM is potentially faster than some existing image CS reconstruction methods.

• Journal of applied mathematics & informatics
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• v.38 no.5_6
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• pp.519-532
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• 2020

In this paper, we first propose a new total variation-based regularization model for image restoration. We next propose a fixed-point-like method for solving the new image restoration model, and then we provide convergence analysis for the fixed-point-like method. To evaluate the feasibility and efficiency of the fixed-point-like method for the new proposed total variation-based regularization model, we provide numerical experiments for several test problems.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.270-273
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• 2007

In this paper, a SAR-despeck1ing approach of adaptive iteration based a Bayesian model using the lognormal distribution for image intensity and a Gibbs random field (GRF) for image texture is proposed for noise removal of the images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. The iterative approach based on MRF is very effective for the inner areas of regions in the observed scene, but may result in yielding false reconstruction around the boundaries due to using wrong information of adjacent regions with different characteristics. The proposed method suggests an adaptive approach using variable parameters depending on the location of reconstructed area, that is, how near to the boundary. The proximity of boundary is estimated by the statistics based on edge value, standard deviation, entropy, and the 4th moment of intensity distribution.

• Journal of Broadcast Engineering
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• v.6 no.2
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• pp.177-186
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• 2001

A digital watermark Is a perceptually unobtrusive signal embedded in some multimedia asset such as an Image for copyright protection. In many cases watermark detection amounts to thresholding a correlation vague between a watermark and a received image. Watermarking detection schemes can be classified into two types. Type 1 is based on a correlation process that is applied to the difference between an original image and an input Image to be tested. Type 2 is based on a correlation process that is directly applied to an input Image. The type 1 fails to prove the rightful ownership, while type 2 has an advantage in terms of rightful ownership compared with type 1. However, type 2 has a problem that doesnt appear in type 1. The problem is that correlation between a watermark and an original Image to be watermarked is trio significant to be ignored, when it Is normalized by watermarks energy. In this paper, based on the analysis of the correlation, we propose a novel watermarking scheme to minimize the effect and also verify the performance of the proposed scheme by experiments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.189-197
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• 2012

This research attempted to find possibilities of the practical use utilizing geospatial methods for the balanced promotion of sustainable coastal development and preservation through a case study of Jekyll Island, one of Georgia's barrier islands. In response, this research provided ways for practical use in sustainable development and preservation plans. First this research thoroughly investigated the 1996 master plan of Jekyll Island and tried to recalculate developed and undeveloped areas. Second, new estimations for developed areas were investigated through field survey. Third, this research proposed the use of the satellite images with different levels of spatial resolutions and tested different classification schemes to find possibilities for practical use. For these purposes, first, we classified developed and undeveloped features by manual digitization using an aerial photo image with 0.5m spatial resolution. Second, a Landsat 7 ETM+ and a QuickBird satellite images with mid- and high-levels of spatial resolutions were applied to identify developed and undeveloped areas using both the National Land Cover Data (NLCD) and the Coastal Change Analysis Program (CCAP) classification schemes. Also, GEOBIA (Geographic Object-Based Image Analysis) was conducted to accurately identify developed and undeveloped areas.

• Fashion & Textile Research Journal
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• v.21 no.1
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• pp.27-35
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• 2019

Fashion Influencer of Instagram get a lot of attention from the public, and they play a major role in shaping peoples' taste. This study attempts to analyze the fashion design of fashion influencer in Instagram. The data was collected from Apr. 15th to April 30th, 2017, and the pictures were collected from May, 2016 to April, 2017. Total of 460 pictures were collected based on the number of "likes". The method of study was content analysis and the cross tabulation analysis and frequency using SPSS Statics 24 Based on the above results, influencers were mostly models that have many "likes" on their photos. Many of influencers were wearing black, white, or blue dresses that do not have any patterns. Many others were wearing indigo, black, or white jeans with T-shirts. In summary of the above contents, influencer also found out that the materials of their clothes were both hard and soft, and that the casual style was the most popular among influencer, and that influencer also liked elegant, modern, mannish, or sexy looks. Therefore, through this study, it was found that the fashion design of influencer had a unique fashion image. Gigi Hadid, Kendall Jenner, and Blake Lively are the representative influencers of fashion instagram. Gigi Hadid was a casual and manish image, Kendall Jenner was a casual and sexy image, and Blake Lively was an elegant image.

• Journal of The Korean Society of Integrative Medicine
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• v.8 no.3
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• pp.103-112
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• 2020

Purpose : This study aims to investigate social welfare and students' image of social workers and determine the relevance of these factors to the academic system, gender, and their motivations when selecting a major. Methods : For this study, social welfare students from two two-year colleges and two four-year universities were randomly selected, and 320 students from social welfare departments who understood and agreed to participate in the research took the survey. The data analysis of this study was conducted using SPSS 23.0. Results : The Social Welfare Department students' perception of a social worker's image was shown to be positive. In the social worker image based on academic background, the first grade was found to be more positive than the second, third, and fourth grades. The professional image was more positive than the traditional, social, and vocational images. The gender-based social worker image showed that females were more positive than males. Females were more positive for the professional image, and males were more positive for the traditional image. Regarding the image of social workers based on students' motivation when choosing their major, it was found that volunteer jobs were more positive in terms of traditional images, social images through recommendations, and professional images with aptitude and interest. Conclusion : In sum, most of the students in the social welfare departments had a positive perception of the social worker position. They had a more positive image at the time of admission. Finally, students who entered the school with an expert awareness of social welfare were more positive.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.626-629
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• 2004

Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program for GLCM algorithm is newly implemented in the MS Visual IDE environment. While, additional texture imaging modules based on GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV texture variables, it composed of six types of second order texture function in the several quantization levels of 2(binary image), 8, and 16: Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality, four directions are provided as $E-W(0^{\circ}),\;N-E(45^{\circ}),\;S-W(135^{\circ}),\;and\;N-S(90^{\circ}),$ and W-E direction is also considered in the negative direction of E- W direction. While, two direction modes are provided in this program: Omni-mode and Circular mode. Omni-mode is to compute all direction to avoid directionality problem, and circular direction is to compute texture variables by circular direction surrounding target pixel. At the second phase of this study, some examples with artificial image and actual satellite imagery are carried out to demonstrate effectiveness of texture imaging or to help texture image interpretation. As the reference, most previous studies related to texture image analysis have been used for the classification purpose, but this study aims at the creation and general uses of texture image for urban remote sensing.