• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.570-595
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• 2017

Robust and perceptually-adaptive image watermarking algorithms have mainly targeted gray-scale images either at the modeling or embedding levels despite the widespread availability of color images. Only few of the existing algorithms are specifically designed for color images where color correlation and perception are constructively exploited. In this paper, a new perceptual and high-capacity color image watermarking solution is proposed based on the extension of Tsui et al. algorithm. The $CIEL^*a^*b^*$ space and the spatio-chromatic Fourier transform (SCFT) are combined along with a perceptual model to hide watermarks in color images where the embedding process reconciles between the conflicting requirements of digital watermarking. The perceptual model, based on an emerging color image model, exploits the non-uniform just-noticeable color difference (NUJNCD) thresholds of the $CIEL^*a^*b^*$ space. Also, spread-spectrum techniques and semi-random low-density parity check codes (SR-LDPC) are used to boost the watermark robustness and capacity. Unlike, existing color-based models, the data hiding capacity of our scheme relies on a game-theoretic model where upper bounds for watermark embedding are derived. Finally, the proposed watermarking solution outperforms existing color-based watermarking schemes in terms of robustness to standard image/color attacks, hiding capacity and imperceptibility.

• Journal of The Korea Institute of Healthcare Architecture
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• v.13 no.2
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• pp.27-36
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• 2007

Recently, hospital patients experience anxiety, confusion, and stress about wayfinding as the spacial layout and treatment circulatory system of hospitals have become complicated due to their oversized and complex structure. As part of finding a solution to the problem, this study seeks to examine what are the essential elements of the wayfinding planning of O.P.D. in general hospitals, to develop the model of wayfinding, and to suggest the methods of improving the wayfinding system. The research methods of this study adopted were literature review in wayfinding cognition, plan analysis of ten general hospitals, space analysis of these hospitals through space syntax, analysis of the system of visual-perceptual information through a field study, and analysis of surveys and follow-up surveys conducted to support the results. Based on these results, the proposals for finding decision points, providing the information, and developing a model planning are listed as follows. 1) The comprehensive understanding of O.P.D. spacial layout and the visual-perceptual information system is necessary to find the essential elements of wayfinding. 2) The decision points are found through the full understanding of spacial functions, circulation systems, and facility configuration, considering the spacial layout, the bound of the visual-perceptual information system, and the circulatory system. Furthermore, the information decision points could be confined by space syntax. 3) The checklist and color compound & color codes, developed through the planning of signage system and color system could be applied to the methods of providing the information. 4) The planning of wayfinding system according to the whole process of practices for outpatients was mentioned above. The system of visual-perceptual information developed through the process of this study should be integrated in the spacial layout of the whole O.P.D.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.260-263
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• 2016

Recently high dynamic range imaging technique is hot issue in computer graphic area. We present a progressive tone mapping algorithm, which is based on weighted least squares optimization framework. Our approach combines weighted leastsquaresfiltering with iCAM06, for showing more perceptual high dynamic range images in conventional display, while avoiding visual halo artifacts. We decompose high dynamic range image into base layer and detail layer. The base layer has large scale variation, it is obtained by using weighted least squares filtering, and then the base layer incorporates iCAM06 model. Then, adaptive compression on the base layer according to human visual system. Only the base layer reduces contrast, and preserving detail. The resultshows more perceptual color appearance and preserve fine detail, while avoiding common artifacts.

• Journal of KIISE
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• v.42 no.10
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• pp.1294-1302
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• 2015

A lot of image quality assessment metrics that can precisely reflect the human visual system (HVS) have previously been researched. The Structural SIMilarity (SSIM) index is a remarkable HVS-aware metric that utilizes structural information, since the HVS is sensitive to the overall structure of an image. However, SSIM fails to deal with color difference in terms of the HVS. In order to solve this problem, the Structural and Hue SIMilarity (SHSIM) index has been selected with the Hue, Saturation, Intensity (HSI) model as a color space, but it cannot reflect the HVS-aware color difference between two color images. In this paper, we propose a new image quality assessment method for a color image by using a CIE Lab color space. In addition, by using a support vector machine (SVM) classifier, we also propose an optimization system for applying optimal metric according to the types of distortion. To evaluate the proposed index, a LIVE database, which is the most well-known in the area of image quality assessment, is employed and four criteria are used. Experimental results show that the proposed index is more consistent with the other methods.

• Journal of Information Display
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• v.11 no.1
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• pp.17-20
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• 2010

With the increasing demand for a better FPD image quality, better evaluation metrics and advanced display quality measurement methods are required to meet these needs. There are many measurement methods for evaluating the viewing angle of various display devices, but these methods, which include luminance drop, color shift, and contrast ratio decrease, are imperfect considering that human perception does not completely correlate to them. In this paper, a new method of measuring the perceptual angle of FPDs is proposed, considering human visual perception, which uses the color space of the color appearance model.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.979-982
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• 2009

With increasing demand for better FPD image quality, better evaluation metrics and advanced display quality measurement methods are required to meet these needs. There are many measurement methods to evaluate viewing angle of the various different display devices. However, these methods, which include luminance drop, color shift, and contrast ratio decrease, are imperfect considering that human perception does not completely correlate to these methods. In this paper, we propose a new method for measuring perceptual angle of FPDs considering human visual perception, which uses color space of the color appearance model.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1661-1663
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• 2007

The contrast of display is one of the important specifications. Even if the contrast indicates luminance range which is a capability of the display and is greater in lower luminance or higher luminance, we consider that the greater contrast gets not the better performance. It is not the same value in human visual system. In practice, it is difficult to achieve the full dynamic range seen by human beings using electronic equipment. Therefore, we consider ambient condition and human perception to calculate perceptual contrast using the CIECAM02. In this paper, we propose perceptual contrast that is calculated using the brightness of CIECAM02.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.47-50
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• 2008

We propose a new method evaluating the image quality of display devices using the CIECAM02 that is the recently developed CIE color appearance model and provides an extension of the previously recommended CIE color spaces. We develop the evaluation method that quantifies the color reproduction capability, emotional gray scale (gradation), and visual perception contrast (perceptual contrast range) based on the gamut in this model.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.131-143
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• 2014

We propose a no-reference perceptual fog density and visibility prediction model in a single foggy scene based on natural scene statistics (NSS) and perceptual "fog aware" statistical features. Unlike previous studies, the proposed model predicts fog density without multiple foggy images, without salient objects in a scene including lane markings or traffic signs, without supplementary geographical information using an onboard camera, and without training on human-rated judgments. The proposed fog density and visibility predictor makes use of only measurable deviations from statistical regularities observed in natural foggy and fog-free images. Perceptual "fog aware" statistical features are derived from a corpus of natural foggy and fog-free images by using a spatial NSS model and observed fog characteristics including low contrast, faint color, and shifted luminance. The proposed model not only predicts perceptual fog density for the entire image but also provides local fog density for each patch size. To evaluate the performance of the proposed model against human judgments regarding fog visibility, we executed a human subjective study using a variety of 100 foggy images. Results show that the predicted fog density of the model correlates well with human judgments. The proposed model is a new fog density assessment work based on human visual perceptions. We hope that the proposed model will provide fertile ground for future research not only to enhance the visibility of foggy scenes but also to accurately evaluate the performance of defog algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.