• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.413-422
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• 2018

Many applications using satellite data from high-resolution multispectral sensors require an image fusion step, known as pansharpening, before processing and analyzing the multispectral images when spatial fidelity is crucial. Image fusion methods are to improve images with higher spatial and spectral resolutions by reducing spectral distortion, which occurs on image fusion processing. The image fusion methods can be classified into MRA (Multi-Resolution Analysis) and CSA (Component Substitution Analysis) approaches. To suggest the efficient image fusion method for Pleiades and KOMPSAT (Korea Multi-Purpose Satellite) 3 satellites, this study will evaluate image fusion methods for multispectral and panchromatic images. HPF (High-Pass Filtering), SFIM (Smoothing Filter-based Intensity Modulation), GS (Gram Schmidt), and GSA (Adoptive GS) were selected for MRA and CSA based image fusion methods and applied on multispectral and panchromatic images. Their performances were evaluated using visual and quality index analysis. HPF and SFIM fusion results presented low performance of spatial details. GS and GSA fusion results had enhanced spatial information closer to panchromatic images, but GS produced more spectral distortions on urban structures. This study presented that GSA was effective to improve spatial resolution of multispectral images from Pleiades 1A and KOMPSAT 3.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.5
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• pp.648-657
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• 2004

The purpose of this study was to identify the relationship between avatar image and self-concept of avatar users by utilizing focus group interviews and survey method. The subjects of the focus group interview were Freechal Avatar Club members, while those of the survey were 476 students, who attended middle schools, high schools and colleges at Seoul area. The data were analyzed by frequency, factor analysis, cluster analysis, chi-square test, one-way ANOVA and scheffe test. The main results were summarized as follows. First, the focus group interview revealed that avatar image types, which avatar users made use of, were ideal image, real image and fantastic image. Second, based on the avatar image types of focus group interviews, the researcher made out avatar image question items and conducted factor analysis of the question items: The avatar users pursued ideal image, real image and fantastic image. The avatar users groups were classified into ideal image group, real image group and fantastic image group by employing cluster analysis. Third, all of body-esteem and self-esteem were the highest at real image group, while all of that were the lowest at ideal image group.

• Journal of the Korean Society of Costume
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• v.58 no.10
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• pp.135-147
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• 2008

The purposes of this study were to segment consumers by Korean image perceptions and to investigate the differences among the segmented groups in regard to Korean image preferences in casual wear The subjects of the study were 653 women consumers who lived in Seoul. Data were collected from July to September, 2007. Statistical analyses used in the study were factor analysis, cluster analysis, ANOVA, and Duncan test. The results showed that there were four factors of Korean image perceptions: natural, feminine, passionate, and simple images. Based on the four factors, the consumers were segmented into three groups. They were natural image perception group, low interest group, and feminine image perception group. The results showed that there were significant differences among the segmented groups in regard to Korean image preferences In casual wear. For example, natural image perception group prefer diverse Korean prints, blue and green colors, natural fabrics, and diverse casual types for their Korean image casual wear. In the meanwhile, feminine image perception group generally prefer soft fabrics, red and purple colors in their Korean image casual wear.

• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.3 s.110
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• pp.18-30
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• 2005

Since the 1990s, with the beginning of local autonomy, most Korean cities have tried to establish and reinforce their own identity. The Law on the Planning and the Use of National Land, which took effect in January 2003, requires major and minor cities to manage and develop a city image and a marketing strategy to reflect their current condition. However, many cities continue to experience confusion in implementing urban landscape planning because no efficient and systematic method has been provided for the analysis of a city's image. The absence of systematic analysis methods makes it difficult not only to assess the current condition of a city accurately but also to choose an appropriate policy for the given city. Consequently, many cities suffer excessive trials and errors in implementing the correct policies for their city. The purpose of this study was to analyze the image: of Kongju, which has many historical properties. For this purpose, adjective questionnaires and multi-dimensional scaling (MDS) were made use of in order to assess the city image. The results of this study can be summarized as follows: 1. There are five properties that serve as landmarts lie symbolize Kongju: Muryeong royal tomb, Castle Kong, Mt. Gyeoiryong, Forest Museum, and Kongju National Museum. 2. Based on the citizen survey regarding the city type, Kongju is seen as a historical and an educational city. 3. Based on the image positioning (image spatial plot), Kongju is described as an old and familiar city. There we, however, no landmarks which are in accord with the image of Kongju. It is difficult to establish and reinforce the image of a city with a single element like a landmark However, with steady follow-up research, this study may serve as a systematic and logical model to improve the urban landscape and image.

• Ocean and Polar Research
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• v.35 no.3
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• pp.239-247
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• 2013

Digital image processing is a process to analyze a large volume of information on digital images. In this study, Artemia hatching rate was measured by automatically classifying and counting cysts and larvae based on color imaging data from cyst hatching experiments using an image processing technique. The Artemia hatching rate estimation consists of a series of processes; a step to convert the scanned image data to a binary image data, a process to detect objects and to extract their shape information in the converted image data, an analysis step to choose an optimal discriminant function, and a step to recognize and classify the objects using the function. The function to classify Artemia cysts and larvae is optimally estimated based on the classification performance using the areas and the plan-form factors of the detected objects. The hatching rate using the image data obtained under the different experimental conditions was estimated in the range of 34-48%. It was shown that the maximum difference is about 19.7% and the average root-mean squared difference is about 10.9% as the difference between the results using an automatic counting (this study) and a manual counting were compared. This technique can be applied to biological specimen analysis using similar imaging information.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.487-490
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• 1999

In this paper we propose an efficient content-based image retrieval method using the color and wavelet based features. The color features are extracted from color histograms of the global image and the wavelet based features are extracted from the invariant moments of the high-pass band image through the spatial-frequency analysis of the wavelet transform. The proposed algorithm, called color and wavelet features based query(CWBQ), is composed of two-step query operations for efficient image retrieval: the coarse level filtering operation and the fine level matching operation. In the first filtering operation, the color histogram feature is used to filter out the dissimilar images quickly from a large image database. The second matching operation applies the wavelet based feature to the retained set of images to retrieve all relevant images successfully. The experimental results show that the proposed algorithm yields more improved retrieval accuracy with computationally efficiency than the previous methods.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.99-107
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• 2019

Retinex-based image enhancement is a technique that utilizes the property that the human visual characteristics are sensitive to the difference from the surrounding pixel value rather than the pixel value itself. These Retinex-based algorithms show different characteristics of the improved image depending on the applied color space or gamma correction. In this paper, we set eight different experimental conditions according to the application of color space and gamma correction, and analyze the objective and subjective performance of each Retinex based image enhancement algorithm and apply it to the implementation of Retinex based algorithm. In the case of gamma correction, quantitative low entropy images and low contrast images are obtained. The application of Retinex technique in HSI color space rather than RGB color space is found to be high in overall subjective image quality as well as maintaining color.

• The Research Journal of the Costume Culture
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• v.15 no.1 s.66
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• pp.179-192
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• 2007

The purpose of this study was to investigate the relationship among fashion retail-entertainment, store image and store loyalty. Two hundred eleven who female college students living near Seoul area participated in this study. Two hundred sample used for data analysis. For data analysis, frequency, factor analysis, correlation analysis and multiple regression analysis were used. The results were as follows: First, fashion retail-entertainment had 4 factors such as shopping environment, sales service, dining facilities, and others. Store image composed of psychological image, merchandise mix, customer service, and advertising exposure. Store loyalty had 3 factors; cognitive loyalty, intentional loyalty, emotional loyalty. Second, retail-entertainment factors had positive influences on store image and store loyalty. Third, store image had positively affected on store loyalty. Based on these results, successful strategies for fashion retail-entertainment business would provide.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.812-819
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• 1996

This study was performed to quantify microscopically morphological characteristics of cotton fiber to identify parameters for quality evaluation using image analysis . The image of each fiber was captured by a Pc-based color imaging system using a conventional microscope. Ends of individual cotton fibers were glued on a microscope slide without any tension or straightening. A modified watershed technique was implemented to identify individual convolution segments, which were defined as sections of the fiber bordered by two neighboring convolutions. Length, area and perimeter of each convolution segment were measured directly from the image . Average width, shape factor and number of convolution segments in mm were calculated from the measured parameters. The performance of the image analysis algorithm was compared with visual varieties of cotton . The image analysis results agreed with visual inspection in 89.6% of the tested images.

• Journal of radiological science and technology
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• v.42 no.2
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• pp.119-130
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• 2019

Positron emission tomography (PET) is widely used imaging modality for effective and accurate functional testing and medical diagnosis using radioactive isotopes. However, PET has difficulties in acquiring images with high image quality due to constraints such as the amount of radioactive isotopes injected into the patient, the detection time, the characteristics of the detector, and the patient's motion. In order to overcome this problem, we have succeeded to improve the image quality by using the dynamic image reconstruction method based on singular value decomposition. However, there is still some question about the characteristics of the proposed technique. In this study, the characteristics of reconstruction method based on singular value decomposition was estimated over computational simulation. As a result, we confirmed that the singular value decomposition based reconstruction technique distinguishes the images well when the signal - to - noise ratio of the input image is more than 20 decibels and the feature vector angle is more than 60 degrees. In addition, the proposed methode to estimate the characteristics of reconstruction technique can be applied to other spatio-temporal feature based dynamic image reconstruction techniques. The deduced conclusion of this study can be useful guideline to apply medical image into SVD based dynamic image reconstruction technique to improve the accuracy of medical diagnosis.