• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.376-381
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• 2009

The image data compression, recognition, restoration, etc. are parts of the digital image processing technology. In the process by various devices, noises would be made. Because the noise could damage the image, we use the image filter to preserve the original image from the noise. The image filter used in digital image process basically has a two-dimensional structure. There an two methods of creating the filter - One is reiterating one dimension and the other is using an indivisible two-dimension image filter. The image filter is being widely used along with one-dimension filter according to each noise, and various median filters are being used to remove the impulse noise. In this paper, I suggested a powerful modified median filter, and compared with conventional filters for objective verification.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.303-308
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• 2018

In copyright rights of the digital image, copyright holders need to protect copyrights and improve the improvement of copyright laws through accurate understanding of copyright laws, and also to improve the effectiveness of copyright rights of copyright holders and the effectiveness of users' rights. First of all, the scope of the study is based on the case of recognition of the scope of the identity of the same scope and the copyright on the copyright law of the digital image, and the application of the image of the image of the image-writing image and the use of image artifacts based on the image copyright classification system suitable for the user's application.

• ETRI Journal
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• v.39 no.2
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• pp.173-180
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• 2017

Multimodal medical image fusion is the process of retrieving valuable information from medical images. The primary goal of medical image fusion is to combine several images obtained from various sources into a distinct image suitable for improved diagnosis. Complexity in medical images is higher, and many soft computing methods are applied by researchers to process them. Intuitionistic fuzzy sets are more appropriate for medical images because the images have many uncertainties. In this paper, a new method, based on Sugeno's intuitionistic fuzzy set (SIFS), is proposed. First, medical images are converted into Sugeno's intuitionistic fuzzy image (SIFI). An exponential intuitionistic fuzzy entropy calculates the optimum values of membership, non-membership, and hesitation degree functions. Then, the two SIFIs are disintegrated into image blocks for calculating the count of blackness and whiteness of the blocks. Finally, the fused image is rebuilt from the recombination of SIFI image blocks. The efficiency of the use of SIFS in multimodal medical image fusion is demonstrated on several pairs of images and the results are compared with existing studies in recent literature.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.2 s.150
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• pp.326-337
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• 2006

Self-immersed narcissism image that had been limited only a feminine image has being represented as a new masculinity image through various fashion magazine and TV advertisements. Besides, this makes a contribution of enlargement of concern about the beauty and fashion of the male. In the past, fashion has been created through the fetishism about the female body. But, new male image has been changed during only 30-40 years compared with the traditional various social, cultural, sexual body images had been changed for a long time. On the contrary, changed modem male image removes the interval of difference between the male and the female image. Now, representative techniques of the masculinity perform both accommodation and disobedience against social and cultural rules. Social body, which has been understood that appearance represents almost all things, makes the good use of the space of discipline and reformation. This paper is tended to grasp the characteristics of male body image expressed modem male fashion and TV advertisements based on the examination about the changed male body image.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.1
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• pp.117-121
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• 2009

The fisheye image acquired with a fisheye camera has wider field of view than a general use camera. But large distortion of the object in the image requires conversion of the fisheye image to the perspective image because of user's difficult perception. The existing Ishii's method[1] has the problem that the object can has sire and geometrical distortion in the transformed image because it uses equidistance projection. This paper presented a conversion technique of the fisheye image to the perspective image using sealing function. In the experiments, it was shown that our method reduced size and geometrical distortion by applying the scaling function.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.172-179
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• 2015

Because of the development of computers and high-technology applications, all devices that we use have become more intelligent. In recent years, security and surveillance systems have become more complicated as well. Before new technologies included video surveillance systems, security cameras were used only for recording events as they occurred, and a human had to analyze the recorded data. Nowadays, computers are used for video analytics, and video surveillance systems have become more autonomous and automated. The types of security cameras have also changed, and the market offers different kinds of cameras with integrated software. Even though there is a variety of hardware, their capabilities leave a lot to be desired. Therefore, this drawback is trying to compensate by dint of computer program solutions. Image processing is a very important part of video surveillance and security systems. Capturing an image exactly as it appears in the real world is difficult if not impossible. There is always noise to deal with. This is caused by the graininess of the emulsion, low resolution of the camera sensors, motion blur caused by movements and drag, focus problems, depth-of-field issues, or the imperfect nature of the camera lens. This paper reviews image processing, pattern recognition, and image digitization techniques, which will be useful in security services, to analyze bio-images, for image restoration, and for object classification.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.362-367
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• 2018

A complementary metal oxide semiconductor (CMOS) binary image sensor is proposed for low-power and low-noise operation. The proposed binary image sensor has the advantages of reduced power consumption and fixed pattern noise (FPN). A gate/body-tied (GBT) p-channel metal-oxide-semiconductor field-effect transistor (PMOSFET)-type photodetector is used as the proposed CMOS binary image sensor. The GBT PMOSFET-type photodetector has a floating gate that amplifies the photocurrent generated by incident light. Therefore, the sensitivity of the GBT PMOSFET-type photodetector is higher than that of other photodetectors. The proposed CMOS binary image sensor consists of a pixel array with $394(H){\times}250(V)$ pixels, scanners, bias circuits, and column parallel readout circuits for binary image processing. The proposed CMOS binary image sensor was analyzed by simulation. Using the dynamic comparator, a power consumption reduction of approximately 99.7% was achieved, and this performance was verified by the simulation by comparing the results with those of a two-stage comparator. Also, it was confirmed using simulation that the FPN of the proposed CMOS binary image sensor was successfully reduced by use of the double sampling process.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.17-22
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• 2021

Recently, image super-resolution techniques used in convolutional neural networks (CNN) have led to remarkable performance in the research area of digital image processing applications and computer vision tasks. Convolutional layers stacked on top of each other can design a more complex network architecture, but they also use more memory in terms of the number of parameters and introduce the vanishing gradient problem during training. Furthermore, earlier approaches of single image super-resolution used interpolation technique as a pre-processing stage to upscale the low-resolution image into HR image. The design of these approaches is simple, but not effective and insert the newer unwanted pixels (noises) in the reconstructed HR image. In this paper, authors are propose a novel single image super-resolution architecture based on synchronized depthwise separable convolution with Dense Skip Connection Block (DSCB). In addition, unlike existing SR methods that only rely on single path, but our proposed method used the synchronizes path for generating the SISR image. Extensive quantitative and qualitative experiments show that our method (SDCN) achieves promising improvements than other state-of-the-art methods.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.70.4-70.4
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• 2019

Image super-resolution (SR) is a technique that enhances the resolution of a low resolution image. In this study, we use three SR models (RCAN, ProSRGAN and Bicubic) for enhancing solar SDO/HMI magnetograms using deep learning. Each model generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). The pixel resolution of HMI is about 0.504 arcsec. Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained three models with HMI images in 2014 and test them with HMI images in 2015. We find that the RCAN model achieves higher quality results than the other two methods in view of both visual aspects and metrics: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is also much better than the conventional bi-cubic interpolation. We apply this model to a full-resolution SDO/HMI image and compare the generated image with the corresponding Hinode NFI magnetogram. As a result, we get a very high correlation (0.92) between the generated SR magnetogram and the Hinode one.

• Journal of Korean Academy of Nursing Administration
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• v.11 no.1
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• pp.59-66
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• 2005

Purpose: The purpose of this study was to identify the effects images about medical organizations and the quality of service on customer satisfaction of obs and gyn patients. Method: The subjects of this study were selected conveniently 220 women among obstetrics and gynecology outpatients( who visited H- doctor's office of the first medical organ, P- hospital of the second medical organization, Chospital of the third medical organization). The data were collected from August, 20th 2004 using structured questionaires which included modified form of SERVPERF and customer's satisfaction scale by oliver & swan(1989), and modified form of image scale by kang(1997). Results: Image of hospital(45.3%), visiting frequencies(9.3%), service provider (3.9%) and convenient use(1.2%) of the quality of medical service were significant predictors to explain customer's satisfaction. Conclusion: To increase customer's satisfaction of obs and gyn patients, it is required to developed strategies that improve image of hospital and the quality of service to service provider and convenient use of hospital.