• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.3
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• pp.313-322
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• 2000

The purpose of this study was to investigate the characteristic and image of oriental costume designs which represented among three countries, Korea, China and Japan. The specific objectives were: 1) to find out the positioning of oriental costume design. 2) to find out relation to oriental costume image and preference. The stimulus were 75 costume designs of contemporary costume which represented the traditional images of three countries Korea, China and Japan. The main survey of questionary consisted of their evaluation of the oriental costume image by 26 semantic differential bi-polar scales and the subjects were 99 female students majoring in clothing and textile. The data were analyzed by Multidimensional Scaling Method and Regression Analysis. The specific objective were as follows: 1. According to image positioning. The oriental costume design was classified by simple-decorative, soft-hard. 2. As result of regression analysis. The preference of oriental costume image was related to attractive factor.

• Journal of the Optical Society of Korea
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• v.16 no.3
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• pp.270-276
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• 2012

An off-axis integral floating system using a concave mirror is analyzed to resolve the image distortion incurred by the off-axis optical arrangement. The concave mirror can be adopted as the floating device to improve the optical efficiency. The image distortion due to the tilting axis of the concave mirror needs to be analyzed precisely to generate the pre-distortion image. In this paper, we calculate the image deformation in the off-axis structure of the concave mirror using the geometrical optics. Using the calculation results, the compensated elemental image can be generated for the pre-distortion integrated image, which can be projected to the floating 3D image without image distortion. The basic experiments of the off-axis integral floating are presented to prove and verify the proposal.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.187-193
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• 2012

An image authentication scheme for gray scale image through embedding a digital watermark by quantization of Integer Wavelet Transform (IWT) coefficients of the image is proposed in this paper. Proposed method is designed to detect modification of an image and to identify tampered location of the image. To embed the watermark mid-frequency band of a second level IWT was used. An approximation of the original image based on LL band was stored in LSB bits of the pixel data as a recovery mark for restoration of the image. Watermarked image has achieved a good PSNR of 40 dB compared to original cover image. Restored image quality was also very good with a PSNR of more than 35 dB compared to unmodified watermarked image even when 25% of the received image is cropped. Thus, the proposed method ensures a proper balance between the fidelity of the watermarked image and the quality of the restored image.

• The Journal of Korea Robotics Society
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• v.9 no.3
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• pp.170-177
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• 2014

This paper proposes a novel upward-looking camera-based global localization using a ceiling image map. The ceiling images obtained through the SLAM process are integrated into the ceiling image map using a particle filter. Global localization is performed by matching the ceiling image map with the current ceiling image using SURF keypoint correspondences. The robot pose is then estimated by the coordinate transformation from the ceiling image map to the global coordinate system. A series of experiments show that the proposed method is robust in real environments.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1164-1171
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• 2015

The edge preserving method is important for image storage and geometric transformation. In this paper, we propose a new edge preserving method using HOG-Guide filter for image segmentation. In our approach, we extract edge information using gradient histogram to set HOG guide line. Then, we use HOG guide line to smooth image. With two to four iterations of smoothing operations, we finally obtain desirable edge preserved image. Our experimental results showed good performances showing that our proposed method is better than other methods.

• Asian Journal for Public Opinion Research
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• v.8 no.2
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• pp.126-143
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• 2020

Since 2008, strategic partnerships have been established between China and Korea. From 2009 to 2019, the bilateral relationship kept a generally stable rate of development with conflicts and uncertainties. It is necessary to study national image construction in the respective mainstream media of the two countries. The present study analyzed Korea-related reports (N = 744) in the People's Daily from 2009 to 2019, aiming to examine the Korean national image framing under Fairclough's three-dimensional Critical Discourse Analysis (CDA) framework: "whatness," "how," and "whyness." The results shed light on what the Korean national image in the People's Daily was and how and why it was framed in that way. This study provided some implications for readers to further recognize the role that media play in constructing a particular image of one country and a frame for researchers to study foreign national image framing in one of China's mainstream newspapers.

• Journal of the Optical Society of Korea
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• v.17 no.2
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• pp.148-161
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• 2013

We propose one- and two-dimensional reference functions for processing of integral/multiview imaging. The functions provide the synthesis/analysis of the integral image by distance, as an alternative to the composition/decomposition by view images (directions). The synthesized image was observed experimentally. In analysis confirmed by simulation in a qualitative sense, the distance was obtained by convolution of the integral image with the reference functions.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.169-172
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• 2005

Genetic algorithm based predictor for lossless image compression is propsed. We describe a genetic algorithm to learn predictive model for lossless image compression. The error image can be further compressed using entropy coding such as Huffman coding or arithmetic coding. We show that the proposed algorithm can be feasible to lossless image compression algorithm.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1223-1232
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• 2019

The injection is the input method of the image feature vector from the encoder to the decoder. Since the image feature vector contains object details such as color and texture, it is essential to generate image captions. However, the bidirectional decoder model using the existing injection method only inputs the image feature vector in the first step, so image feature vectors of the backward sequence are vanishing. This problem makes it difficult to describe the context in detail. Therefore, in this paper, we propose the parallel injection method to improve the description performance of image captions. The proposed Injection method fuses all embeddings and image vectors to preserve the context. Also, We optimize our image caption model with Bidirectional Gated Recurrent Unit (Bi-GRU) to reduce the amount of computation of the decoder. To validate the proposed model, experiments were conducted with a certified image caption dataset, demonstrating excellence in comparison with the latest models using BLEU and METEOR scores. The proposed model improved the BLEU score up to 20.2 points and the METEOR score up to 3.65 points compared to the existing caption model.