• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.83-86
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• 1995

Many image display devices allow only a limited number of colors to be simultaneously displayed. In displaying of natural color image using color palette, it is necessary to construct an optimal color palette and map each pixel of the original image to a color palette with fast. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. Same as the clustering process, original color image is mapped to palette color via a local region block centering around prequantized original color value. The proposed algorithm incorporated with a spatial activity weighting value which is smoothing region. The method produces high quality display images and considerably reduces computation time.

• Journal of Broadcast Engineering
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• v.1 no.1
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• pp.22-28
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• 1996

In color indexed images using the palette, the corrupted indices cause serious quality degradation in the reconstructed images at a receiver. In this paper, using the human visual characteristics of color perception, we propose the color image palette minimizing the quality degradation and the reconstruction error. We define the new measure to compare the performance of palette .construction algorithms and show the effectiveness of the proposed method under the bit error condition by computer simulation.

• Journal of Semiconductor Engineering
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• v.2 no.1
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• pp.125-129
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• 2021

As the interest of deep learning, techniques to control the color of images in image processing field are evolving together. However, there is no clear standard for color, and it is not easy to find a way to represent only the color itself like the color-palette. In this paper, we propose a novel color palette extraction system by chroma fine-tuning with reinforcement learning. It helps to recognize the color combination to represent an input image. First, we use RGBY images to create feature maps by transferring the backbone network with well-trained model-weight which is verified at super resolution convolutional neural networks. Second, feature maps are trained to 3 fully connected layers for the color-palette generation with a generative adversarial network (GAN). Third, we use the reinforcement learning method which only changes chroma information of the GAN-output by slightly moving each Y component of YCbCr color gamut of pixel values up and down. The proposed method outperforms existing color palette extraction methods as given the accuracy of 0.9140.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.101-110
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• 1996

Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. the basic problem is how to display 224 colors with 256 or less colors, called color palette. In this paper, we propose an algorithm to design the 256 or less size color palette by using spatial maskin geffect of HVS and subjective distortion measure weighted by color palette by using spatial masking effect of HVS and subjective distortion measure weighted by color activity in 4*4 local region in any color image. The proposed algorithm consists of octal prequantization and subdivision quantization processing step using the distortion measure and modified Otsu's between class variance maximization method. The experimental results show that the proposed algorithm has higher visual quality and needs less consuming time than conventional algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.848-854
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• 1996

Many image display devices allow only a limited number of colors to be simultaneously displayed. in disphaying of natural color image using color palette, it is necessary to construct an optimal color palette and the optimal mapping of each pixed of the original image to a color from the palette. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. The same as the clustering process, original color value. The proposed algorithm incroporated with a spatial activity weighting value which is reflected sensitivity of HVS quantization errors in smoothing region. This method produces high quality display images and considerably reduces computation time.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.12
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• pp.31-41
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• 2019

Biophilic design gives human beings positive and valuable experiences in nature. The experience in nature in the architectural environment is mainly symbolic and metaphorical, and is based on visual sensations such as color, form, and image. Recently, modern people living in a modern and simple style indoor space have a desire to pursue visual stimuli for interest or pleasure. This desire can be satisfied through color, lighting, and finishing plan. Therefore, the purpose of this study is to propose a biophilic design color palette based on the empirical characteristics and properties of biophilic design. The methods used in this study are as follows. First, the biophilic design factors and natural landscape preference criteria are examined. Second, based on the review results, natural landscape images are selected and color information for each biophilic design element is extracted according to the vertical and horizontal directions. Third, color information is converted to NCS color code and palette range and hue range are derived through the analysis of ratio and average values. Finally, based on the analysis results, biophilic design color palette is proposed for each element. The results of this study might be useful as basic data in establishing biophilic design strategies and applying them to architecture and interior construction.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.569-574
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• 1999

New methods for both color palette design and dithering based on human visual system (HVS) characteristics are proposed. Color quantization for palette design uses the relative visual sensitivity and spatial masking effect of HVS. The dithering operation for printing uses nonlinear quantization, which considers the overlapping phenomena among neighbor printing dots, and then a modified dot-diffusion algorithm is followed to compensate the degradation produced in the quantization process. The proposed techniques can produce high quality image in the low-bit color devices.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.7
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• pp.340-353
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• 2008

A computational color palette extraction model is introduced to describe paint brush objectively and efficiently. In this model, a color palette is defined as a minimum set of colors in which a painting can be displayed within error allowance and extracted by the two step processing of color grouping and major color extraction. The color grouping controls the resolution of colors adaptively and produces a basic color set of given painting images. The final palette is obtained from the basic color set by applying weighted k-means clustering algorithm. The extracted palettes from several famous painters are displayed in a 3-D color space to show the distinctive palette styles using RGB and CIE LAB color models individually. And the two experiments of painter classification and color transform of photographic image has been done to check the performance of the proposed method. The results shows the possibility that the proposed palette model can be a computational color analysis metric to describe the paint brush, and can be a color transform tool for computer graphics.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.169-173
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• 2008

A navigation system for virtual environments using low-quality HMD(head mounted display) must quantize images when the system presents true-color image with restricted number of colors. Such navigation system quantizes an image by using fixed palette. If the system represents an image by using a variable palette which is made considering a region around the viewpoint then user can perceive a virtual environments more vividly because human visual system is sensitive to the colors variation in the region around the viewpoint. In this paper we propose a color quantization algorithm that quantize a region around the viewpoint more finely than other regions at each variation of viewpoint for virtual environments navigation system.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2002.04a
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• pp.154-158
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• 2002

The object of this study is to find out our present exterior color palette of the apartment buildings by Han River, which represents the visual image of Seoul, to reveal how well it is harmonized with its surroundings along with the last 10 years researches, and to compare its correspondence with the city plan of Seoul. Furthermore, it is the ultimate purpose to prepare source materials for desirable color plan of the city.