• Journal of Korean Clinical Health Science
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• v.5 no.3
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• pp.888-896
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• 2017

Purpose. The purpose of this study was to investigate the effect of visual field training on visual function, visual perception and attention enhancement. Methods. We examined the changes of visual function and visual perception tests for children with mild developmental disabilities through vision therapy. Results. At the time of the initial visit of the child, the ability to control not only distant and near visual function, but also accommodation, was also very limited. Also, the visual perception score was measured at 80 points. Through vision therapy, it was confirmed that the improvement of control ability as well as the visual function and visual perception function test results were also improved to 108 points. Conclusion. It was confirmed that vision therapy results in an improvement of visual function, improved visual perception ability, as well as visual perception ability, It was concluded that visual function affected visual perception, and that vision therapy used in order to prevent visual function deterioration was found to be very helpful.

• ETRI Journal
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• v.39 no.1
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• pp.76-86
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• 2017

In this study, we propose an automatic contrast enhancement method based on transfer function modification (TFM) by histogram equalization. Previous histogram-based global contrast enhancement techniques employ histogram modification, whereas we propose a direct TFM technique that considers the mean brightness of an image during contrast enhancement. The mean point shifting method using a transfer function is proposed to preserve the mean brightness of an image. In addition, the linearization of transfer function technique, which has a histogram flattening effect, is designed to reduce visual artifacts. An attenuation factor is automatically determined using the maximum value of the probability density function in an image to control its rate of contrast. A new quantitative measurement method called sparsity of a histogram is proposed to obtain a better objective comparison relative to previous global contrast enhancement methods. According to our experimental results, we demonstrated the performance of our proposed method based on generalized measures and the newly proposed measurement.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1233-1243
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• 2015

The contrast enhancement is great challenge in the image processing when images are suffering from poor contrast problem. Therefore, in order to overcome this problem an automatic method is proposed for contrast enhancement of natural color images. The proposed method consist of two stages: in first stage lightness component in YIQ color space is normalized by sigmoid function after the adaptive histogram equalization is applied on Y component and in second stage automatic color contrast enhancement algorithm is applied on output of the first stage. The proposed algorithm is tested on different NASA color images, hyperspectral color images and other types of natural color images. The performance of proposed algorithm is evaluated and compared with the other existing contrast enhancement algorithms in terms of colorfulness metric and color enhancement factor. The higher values of colorfulness metric and color enhancement factor imply that the visual quality of the enhanced image is good. Simulation results demonstrate that proposed algorithm provides higher values of colorfulness metric and color enhancement factor as compared to other existing contrast enhancement algorithms. The proposed algorithm also provides better visual enhancement results as compared with the other existing contrast enhancement algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.837-856
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• 2016

Underwater image enhancement has received considerable attention in last decades, due to the nature of poor visibility and low contrast of underwater images. In this paper, we propose a new automatic underwater image enhancement algorithm, which combines nonsubsampled contourlet transform (NSCT) domain enhancement techniques with the mechanism of the human visual system (HVS). We apply the multiscale retinex algorithm based on the HVS into NSCT domain in order to eliminate the non-uniform illumination, and adopt the threshold denoising technique to suppress underwater noise. Our proposed algorithm incorporates the luminance masking and contrast masking characteristics of the HVS into NSCT domain to yield the new HVS-based NSCT. Moreover, we define two nonlinear mapping functions. The first one is used to manipulate the HVS-based NSCT contrast coefficients to enhance the edges. The second one is a gain function which modifies the lowpass subband coefficients to adjust the global dynamic range. As a result, our algorithm can achieve contrast enhancement, image denoising and edge sharpening automatically and simultaneously. Experimental results illustrate that our proposed algorithm has better enhancement performance than state-of-the-art algorithms both in subjective evaluation and quantitative assessment. In addition, our algorithm can automatically achieve underwater image enhancement without any parameter tuning.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.70-75
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• 2022

With the spread of various digital devices, devices have become commonplace in modern society. Moreover, due to the increase in device usage and online learning while staying indoors during the COVID-19 pandemic, symptoms such as an increase in myopia in children due to eye fatigue, an increase in young presbyopia, and dry eye syndrome are increasing, and now people are paying attention to eye health. This is different from before. There are various prescriptions for eye health, but in this paper, we would like to propose a training method for enhancing visual function using VR contents. The analog methods of the existing teaching aids for visual function reinforcement training were planned and produced as digital contents, and VR-based training contents were selected from among the various methods carried out with teaching aids at the visual function training center, which can be made into contents. was developed with In the training process for each content, it was proposed to apply eye tracking to the VR device in order to give the user feedback on their participation in the training so that the management and concentration of the training process could be analyzed.

• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1187-1194
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• 2005

In this paper, new contrast enhancement algorithms that use temporal decimation method and approximated CDF(Cumulative Distribution Function) are proposed. They reduce the amount of computation which is required for image contrast enhancement. Simulation results show that the algorithms can achieve significant reduction in the computational cost and the hardware complexity. Visual test and standard deviation of their histogram have been introduced to evaluate the resultant output images of the proposed method and the original ones.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.69-74
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• 1995

An object color can be seen differently under the various outer illuminants. However, human visual system has color constancy that the object color can be seen constantly under the different outer illuminants. When the viewer watches TV under specific outer illuminants, he perceives distorted color due to the emitting spectrum of outer illuminants as well as the radiation of CPT itself. Namely, when the outer illuminants such as fluorescent and incandescent lamps incident on CPT, brightness, saturation, hue, and contrast on color pictures are changed, he perceives distorted color from the original color. In this paper color enhancement algorithm based on light intensity and outer light decision function using RGB sensor was proposed. The implemented TV of proposed algorithm has higher visual quality at the view point of human visual system and more vivid than that of conventional color TV.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.1
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• pp.22-29
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• 2008

In this paper, we propose an adaptive color enhancement algorithm. It is used for the flat panel displays (FPDs) such as LCD, PDP, and so on. The proposed algorithm consists of an adaptive linear approximation CDF(Cumulative Density Function) algorithm and an adaptive saturation enhancement algorithm. The one is for contrast enhancement which prevents an image from the distortion by luminance transient of an input image. The other is the algorithm which improves the saturation without the contour artifact and over-saturation, whose problems are generated during the enhancing saturation. In addition, it allows to achieve the high quality image using the saturation enhancement method for a preferred color of original image. Visual test and standard deviation of their histograms have been applied to evaluate the resultant output images of the proposed algorithm.

• Journal of Korea Multimedia Society
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• v.24 no.7
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• pp.880-889
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• 2021

In everyday life, recognizing people's emotions from their frames is essential and is a popular research domain in the area of computer vision. Visual emotion has a severe class imbalance in which most of the data are distributed in specific categories. The existing methods do not consider class imbalance and used accuracy as the performance metric, which is not suitable for evaluating the performance of the imbalanced dataset. Therefore, we proposed a method for recognizing visual emotion using balanced data augmentation to address the class imbalance. The proposed method generates a balanced dataset by adopting the random over-sampling and image transformation methods. Also, the proposed method uses the Focal loss as a loss function, which can mitigate the class imbalance by down weighting the well-classified samples. EfficientNet, which is the state-of-the-art method for image classification is used to recognize visual emotion. We compare the performance of the proposed method with that of conventional methods by using a public dataset. The experimental results show that the proposed method increases the F1 score by 40% compared with the method without data augmentation, mitigating class imbalance without loss of classification accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5998-6016
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• 2017

In thin-film transistor liquid-crystal displays (TFT-LCDs), which are most commonly used in mobile devices, the backlight accounts for about 70% of the power consumption. Therefore, most low-power-related studies focus on realizing power savings through backlight dimming. Image compensation is performed to mitigate the visual distortion caused by the backlight dimming. Therefore, popular techniques include pixel compensation for brightness recovery and contrast enhancement, such as histogram equalization. However, existing pixel compensation techniques often have limitations with respect to blur owing to the pixel saturation phenomenon, or because contrast enhancement cannot adequately satisfy the human visual system (HVS). To overcome these, in this study, we propose a novel dimming technique to achieve both power saving and HVS-awareness by combining the pixel compensation and histogram specifications, which convert the original cumulative density function (CDF) by designing and using the desired CDF of an image. Because the process of obtaining the desired CDF is customized to consider image characteristics, histogram specification is found to achieve better HVS-awareness than histogram equalization. For the experiments, we employ the LIVE image database, and we use the structural similarity (SSIM) index to measure the degree of visual satisfaction. The experimental results show that the proposed technique achieves up to 15.9% increase in the SSIM index compared with existing dimming techniques that use pixel compensation and histogram equalization in the case of the same low-power ratio. Further, the results indicate that it achieves improved HVS-awareness and increased power saving concurrently compared with previous techniques.