• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.1
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• pp.33-39
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• 2016

Color image dehazing techniques have been extensively studied, and especially the dark channel prior (DCP)-based method has been widely used. Near infrared (NIR) image based applications are also widespread; however, NIR image-specific dehazing techniques have not attracted great interest. In this paper, the characteristics of NIR images are analyzed and compared with the color images' characteristics. The conventional color image dehazing method is also applied to NIR images to understand its effectiveness on different frequency-band signals. Furthermore, we modify the DCP method considering the characteristics of NIR images and show that our proposed method results in improved dehazed NIR images.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.575-586
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• 2022

Uneven light in real-world causes visual degradation for underexposed regions. For these regions, insufficient consideration during enhancement procedure will result in over-/under-exposure, loss of details and color distortion. Confronting such challenges, an unsupervised low-light image enhancement network is proposed in this paper based on the guidance of the unpaired low-/normal-light images. The key components in our network include super-resolution module (SRM), a GAN-based low-light image enhancement network (LLIEN), and denoising-scaling module (DSM). The SRM improves the resolution of the low-light input images before illumination enhancement. Such design philosophy improves the effectiveness of texture details preservation by operating in high-resolution space. Subsequently, local lightness attention module in LLIEN effectively distinguishes unevenly illuminated areas and puts emphasis on low-light areas, ensuring the spatial consistency of illumination for locally underexposed images. Then, multiple discriminators, i.e., global discriminator, local region discriminator, and color discriminator performs assessment from different perspectives to avoid over-/under-exposure and color distortion, which guides the network to generate images that in line with human aesthetic perception. Finally, the DSM performs noise removal and obtains high-quality enhanced images. Both qualitative and quantitative experiments demonstrate that our approach achieves favorable results, which indicates its superior capacity on illumination and texture details restoration.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07a
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• pp.117-120
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• 2005

The proposed method is based on extracting information from 3-D Fourier spectra calculated from some projection incoherent images. Three colored computer-generated holograms (CGHs) are synthesized from 3-D Fourier spectra. Optically reconstructed full-color images are presented.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.65-84
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• 2006

In this paper, we present an improved image formation model and propose a color image enhancement based on the model. In the presented image formation model, an input image is represented as a product of global illumination, local illumination, and reflectance. In the proposed color image enhancement, an input RGB color image is converted into an HSV color image. Under the assumption of white-light illumination, the H and S component images are remained as they are and the V component image only is enhanced based on the image formation model. The global illumination is estimated by applying a linear LPF with wide support region to the input V component image and the local illumination by applying a JND (just noticeable difference)-based nonlinear LPF with narrow support region to the processed image, where the estimated global illumination is eliminated from the input V component image. The reflectance is estimated by dividing the input V component image by the estimated global and local illuminations. After performing the gamma correction on the three estimated components, the output V component image is obtained from their product. Histogram modeling is next executed such that the final output V component image is obtained. Finally an output RGB color image is obtained from the H and S component images of the input color image and the final output V component image. Experimental results for the test image DB built with color images downloaded from NASA homepage and MPEG-7 CCD color images show that the proposed method gives output color images of very well-increased global and local contrast without halo effect and color shift.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.343-348
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• 2024

Today, AI image creation programs are optimized for various and specialized purposes such as fashion product advertising, customized fashion style suggestions, and design development, and are actively utilized in the fashion industry. Meanwhile, color is a powerful formative element and plays an important role in expressing images for suggesting products or fashion styles. This study seeks to expand understanding of the use of Midjourney by identifying the characteristics of color combinations that appear in clothing images created using Midjourney among AI image creation tools. The results of this study are as follows. First, the initial image created in Midjourney reflects the existing image color used to create the image more than the color specified in the command. Second, the color combinations that appear in the clothes of the images created in Midjourney are divided into separate and mixed colors. The ratio of colors expressed in a separate color scheme is affected by the color order specified in the command. The number of colors combined in a mixed color scheme appears as a combination of fewer colors than the total number of colors of clothing in the existing image used to create the image in Midjourney and the number of colors specified in the command. Third, caution is needed because changes in background color can affect the user's color perception of the clothes in the image and the formation of the costume image. It is hoped that the results of this study will be helpful in fashion design education and practice.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.459-465
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• 2013

This paper is a study on an object extraction method which using color features of an object and background in the image. A human recognizes an object through the color difference of object and background in the image. So we must to emphasize the color's difference that apply to extraction result in this image. Therefore, we have converted to HSV color images which similar to human visual system from original RGB images, and have created two each other images that applied Median Filter and we merged two Median filtered images. And we have applied the Mean Shift algorithm which a data clustering method for clustering color features. Finally, we have normalized 3 image channels to 1 image channel for binarization process. And we have created object map through the binarization which using average value of whole pixels as a threshold. Then, have extracted major object from original image use that object map.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.13-24
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• 2002

This paper presents an automatic approach to detect face and facial feature from face images based on the color information and deformable model. Skin color information has been widely used for face and facial feature diction since it is effective for object recognition and has less computational burden, In this paper, we propose how to compensates varying light condition and utilize the transformed YCbCr color model to detect candidates region of face and facial feature from color images, Moreover, the detected face facial feature areas are subsequently assigned to a initial condition of active contour model to extract optimal boundaries of face and facial feature by resolving initial boundary problem when the active contour is used, The experimental results show the efficiency of the proposed method, The face and facial feature information will be used for face recognition and facial feature descriptor.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.125-137
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• 2011

Recently the research on the system using images taken from camera phones as input is actively conducted. This paper proposed a system that shows wine pictures which are similar to the input wine label in order. For the calculation of the similarity of images, the representative color of each cell of the image, the recognized text color, background color and distribution of feature points are used as the features. In order to calculate the difference of the colors, RGB is converted into CIE-Lab and the feature points are extracted by using Harris Corner Detection Algorithm. The weights of representative color of each cell of image, text color and background color are applied. The image similarity is calculated by normalizing the difference of color similarity and distribution of feature points. After calculating the similarity between the input image and the images in the database, the images in Database are shown in the descent order of the similarity so that the effort of users to search for similar wine labels again from the searched result is reduced.

• Journal of the Korean Society of Fashion and Beauty
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• v.3 no.1 s.4
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• pp.61-71
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• 2005

Everything of the world we live in has its own unique color. Those colors move us, enrich our every day life, and make us happy. When we have our hairs dyed by a color we like, we may look different, feeling confident and activated. We select a color fur our hair color design depending on such symbolic aspects as our life styles, self-images or personalities. Namely, we tend to choose a color the image of which we like. Such a tendency implies that it should be important to study hair colors in multi-faceted ways. The purpose of this study was to survey people's preferences of hair color tone images depending on their demographic and physical variables and thereby, determine the correlations between their preferences and variables. For this purpose, hair colors tones were classified into 11 categories and thereby, subjects' preferences of hair tones were analyzed in terms of the image adjective combinations. The results of this study can be summarized as follows; As a result of analyzing subjects' preferences of hair color tones depending on their such demographic variables as gender, age group and marital status, it was found that males tended to prefer dark tones more than females, and that those in their 30's or older tended to select dark tones more than those in their 20's. On the other hand, the married preferred medium bright tones more than the singles. Furthermore, such physical variables as body size, weight and apparel size were found correlated with hair color tone preferences. To be specific, shorter people desired more to have their hair colors match with their natural ones not to be less exposed to others. Lastly, as a result of analyzing the correlation between hair color tone preferences and weight and apparel size, it was found that fat people tended more to prefer medium bright color tones than normal or slim people.

• FLOWER RESEARCH JOURNAL
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• v.18 no.4
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• pp.308-314
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• 2010

Importance of color in floral design has been emphasized for long time, but it is difficult to find out standardization of color for floral design and for educational system. Wedding bouquet is major and important part of floral design and it shows same problem. The research is concentrated on color image analysis of wedding bouquet designs which have been submitted for 'Interflora World Cup Competition' with the intention to utilize the study result as the basic information of floral design. Colors of wedding bouquets from 20 different countries were analyzed. All of designers chose high brightness and saturation more for designing the bouquets. Warm colors and cold colors have been taken in similar portion. Blue color has been rarely used and it is probably because of the rarity of blue flowers. This study shows each continent has different color preference. European designers used wide variety of colors while Asian designers preferred red color. From this study, we found that color image scales of wedding bouquets represent 8 images out of 12 representative images. Four exceptions are 'clean', 'elegant', 'gentle' and 'modern' images.