• 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.

• Journal of Gastric Cancer
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• v.21 no.2
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• pp.142-154
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• 2021

Purpose: Screening image-enhanced endoscopy for gastrointestinal malignant lesions has progressed. However, the influence of the color enhancement settings for the laser endoscopic system on the visibility of lesions with higher color contrast than their surrounding mucosa has not been established. Materials and Methods: Forty early gastric cancers were retrospectively evaluated using color enhancement settings C1 and C2 for laser endoscopic systems with blue laser imaging (BLI), BLI-bright, and linked color imaging (LCI). The visibilities of the malignant lesions in the stomach with the C1 and C2 color enhancements were scored by expert and non-expert endoscopists and compared, and the color differences between the malignant lesions and the surrounding mucosa were assessed. Results: Early gastric cancers mainly appeared orange-red on LCI and brown on BLI-bright or BLI. The surrounding mucosae were purple on LCI regardless of the color enhancement but brown or pale green with C1 enhancement and dark green with C2 enhancement on BLI-bright or BLI. The mean visibility scores for BLI-bright, BLI, and LCI with C2 enhancement were significantly higher than those with C1 enhancement. The superiority of the C2 enhancement was not demonstrated in the assessments by non-experts, but it was significant for experts using all modes. The C2 color enhancement produced a significantly greater color difference between the malignant lesions and the surrounding mucosa, especially with the use of BLI-bright (P=0.033) and BLI (P<0.001). C2 enhancement tended to be superior regardless of the morphological type, Helicobacter pylori status, or the extension of intestinal metaplasia around the cancer. Conclusions: Appropriate color enhancement settings improve the visibility of malignant lesions in the stomach and color contrast between the malignant lesions and the surrounding mucosa.

• 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 Ocean Engineering and Technology
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• v.34 no.6
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• pp.442-453
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• 2020

Underwater color images suffer from low visibility and color cast effects caused by light attenuation by water and floating particles. This study applied single image enhancement techniques to enhance the quality of underwater images and compared their performance with real underwater images taken in Korean waters. Dark channel prior (DCP), gradient transform, image fusion, and generative adversarial networks (GAN), such as cycleGAN and underwater GAN (UGAN), were considered for single image enhancement. Their performance was evaluated in terms of underwater image quality measure, underwater color image quality evaluation, gray-world assumption, and blur metric. The DCP saturated the underwater images to a specific greenish or bluish color tone and reduced the brightness of the background signal. The gradient transform method with two transmission maps were sensitive to the light source and highlighted the region exposed to light. Although image fusion enabled reasonable color correction, the object details were lost due to the last fusion step. CycleGAN corrected overall color tone relatively well but generated artifacts in the background. UGAN showed good visual quality and obtained the highest scores against all figures of merit (FOMs) by compensating for the colors and visibility compared to the other single enhancement methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.110-117
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• 2016

Applying the contrast enhancement algorithms to luminance values of color images is a widely used approach to enhance the contrast of color images. The results obtained by this approach have reduced saturation compared with that of the original images in spite of contrast enhancement without color degradation. Applying the contrast enhancement algorithm to each channel of color images is another approach for the contrast enhancement of color images. This method produces improved images in terms of contrast and saturation while the hue of original images is changed. In this paper, main cause of color degradation is analyzed and then solving the problem based on the analysis. The channel adaptive contrast enhancement method considering characteristics of each channel is also proposed to deal with color degradation. As a result, the proposed method enhances the contrast and saturation simultaneously without color degradation. Experimental results show that the proposed method outperforms the conventional methods not only on subjective evaluation but on objective criteria.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.770-773
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• 2015

The contrast of the intensity components of color images usually needs to be improved in order to enhance the visual quality of color images. However, pure color regions can be saturated due to the excessive enhancement of that color. In this paper, a new method for enhancing the visual quality of color images using saturation components in the HSI color space is proposed, and the same enhancement technique in the YCbCr color space is proposed. Computer simulations show that the proposed method provides improved visual quality compared to the conventional methods.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.1035-1038
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• 2007

In this paper, we propose a color image improvement method. The proposed algorithms are classified with the adaptive contrast stretching method for contrast enhancement and the adaptive saturation enhancement method for saturation enhancement. The adaptive contrast stretching method is to compensate a significant change of brightness while luminance is processed. The adaptive saturation enhancement method inhibits its saturation from de-saturation and oversaturation while chrominance is processed. The proposed algorithms are focused on a preference color processing in order to generate better image quality than the algorithms focused on a uniform color processing for human vision.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1481-1490
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• 2017

This paper presents an image quality enhancement algorithm for dark image acquired under poor lighting condition. Various retinex algorithms which are human perception-based image processing methods were proposed to solve this problem. Although MSR(Multi-Scale Retinex) among these algorithm works well under most lighting condition, it shows color degradation because their separate nonlinear processing of RGB color channels. To compensate for the loss of the color, MSRCR(Multi-Scale Retinex with Color Restoration) was proposed. However, it requires high computational load and has additional parameters that need to be adjusted according to input image. In order to overcome this problem, a new retinex algorithm based on MSR is proposed in this paper. The proposed method consists of V channel MSR, saturation correction, and separate contrast enhancement process. Experimental results show that the subjective and objective image quality of the proposed method better than those of the conventional methods.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.5-8
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• 2002

The paper handles a skin tone enhancement within digitalized images, which is based on human favorite skin color. To archive a human-favorite skin tone area, lots of observers are participated in visual experiments. The statistical result of the visual experiment was reflected in a proposed skin tone enhancement algorithm and gives more reasonable human-friendly skin color reproduction on a display device. This research was accomplished to implement in our DTV related application.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.99-107
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• 2019

Retinex-based image enhancement is a technique that utilizes the property that the human visual characteristics are sensitive to the difference from the surrounding pixel value rather than the pixel value itself. These Retinex-based algorithms show different characteristics of the improved image depending on the applied color space or gamma correction. In this paper, we set eight different experimental conditions according to the application of color space and gamma correction, and analyze the objective and subjective performance of each Retinex based image enhancement algorithm and apply it to the implementation of Retinex based algorithm. In the case of gamma correction, quantitative low entropy images and low contrast images are obtained. The application of Retinex technique in HSI color space rather than RGB color space is found to be high in overall subjective image quality as well as maintaining color.