• Journal of Electrical Engineering and Technology
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• 제10권3호
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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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• 제21권2호
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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.

• 전기학회논문지P
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• 제57권1호
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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.

• 한국해양공학회지
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• 제34권6호
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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.

• 전자공학회논문지
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• 제53권9호
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• pp.110-117
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• 2016

컬러 영상의 콘트라스트를 향상시키기 위해서 가장 많이 사용되는 방법은 컬러 영상의 밝기 값에 콘트라스트 향상 알고리즘을 적용시키는 것이다. 이 방법은 색상 열화 없이 콘트라스트가 향상된 결과를 얻을 수 있지만, 원본 영상 대비 결과 영상의 채도가 감소되는 문제가 발생한다. 컬러 영상의 콘트라스트를 향상시키기 위한 또 다른 방법은 컬러 영상의 각 채널에 콘트라스트 향상 알고리즘을 적용시키는 것이다. 이 방법은 콘트라스트와 채도가 동시에 향상되지만 색상 열화가 발생하는 단점이 있다. 본 논문에서는 컬러 영상의 각 채널 처리 시 발생하는 색상 열화 원인을 분석하여 이를 보상해주는 방법으로 색상 열화 문제를 해결하였다. 또한 각 채널의 특성을 고려한 채널 적응적 콘트라스트 향상 방법을 이용하여 색상 열화를 방지하는 방법을 제안하였다. 제안하는 방법을 이용하면 컬러 영상의 콘트라스트 향상뿐만 아니라 색상 열화가 발생하지 않으면서 채도가 향상된 결과 영상을 획득할 수 있다. 실험 결과를 통해 제안하는 방법이 주관적 평가뿐 아니라 객관적 평가 지표들에서도 기존 방법들보다 우수한 성능을 보이는 것을 확인 할 수 있다.

• 방송공학회논문지
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• 제20권5호
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• pp.770-773
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• 2015

영상의 화질을 향상시키기 위하여 콘트라스트(contrast)를 향상시키는 기법이 많이 사용된다. 컬러 영상의 콘트라스트를 향상시키는 경우에 컬러의 saturation이 높은 순수한 색에 대해서는 과도한 콘트라스트 향상으로 인한 색 포화 현상이 발생할 수 있다. 본 논문에서는 HSI 컬러 공간에서 saturation 성분을 이용하여 순수한 색에 대한 과도한 콘트라스트 향상으로 발생할 수 있는 색 포화 현상을 방지할 수 있는 기법과 YCbCr 컬러 공간에서도 동일한 효과를 보이는 컬러 영상 화질 향상 기법을 제안한다. 다양한 영상에 대한 실험 결과 제안하는 기법이 기존의 방법에 비하여 좋은 화질의 영상을 생성하는 것을 보인다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권1호
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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.

• 한국멀티미디어학회논문지
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• 제20권9호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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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.

• 디지털산업정보학회논문지
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• 제15권1호
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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.