• 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.

• 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.

• 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.

• 전기학회논문지P
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• 제62권2호
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• pp.90-94
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• 2013

In this paper, we propose a new algorithm to improve the contrast ratio, to preserve information of bright regions and to maintain the color of backlight image that appears with a great relative contrast. Backlight images of the natural environment have characteristics for difference of local brightness; the overall image contrast improvement is not easy. To improve the contrast of the backlight images, MSR (Multi-Scale Retinex) algorithm using the existing multi-scale Gaussian filter is applied. However, existing multi-scale Gaussian filter involves color distortion and information loss of bright regions due to excessive contrast enhancement and noise because of the brightness improvement of dark regions. Moreover, it also increases computational complexity due to the use of multi-scale Gaussian filter. In order to solve these problems, a linear MSR is performed that reduces the amount of computation from the HSV color space preventing the color distortion and information loss due to excessive contrast enhancement. It can also remove the noise of the dark regions which is occurred due to the improved contrast through edge preserving filter. Through experimental evaluation of the average color difference comparison of CIELAB color space and the visual assessment, we have confirmed excellent performance of the proposed algorithm compared to conventional MSR algorithm.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권2호
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• pp.1139-1142
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• 2007

In this paper, an image enhancement method by saturation and contrast improvement is proposed. Histogram equalization with color difference makes higher contrast. By generating saturation amplification ratio with color difference, the saturation improves effectively. The experimental results show that the proposed algorithm has higher contrast and more natural - look than the conventional methods.

• 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.

• 한국멀티미디어학회논문지
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• 제16권1호
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• pp.29-41
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• 2013

디지털 카메라는 제한된 크기의 다이내믹레인지를 갖는 이미지 센서의 한계로 인하여 인간의 눈으로 보는 것과 동일한 화질의 영상을 얻을 수 없기 때문에 이를 개선해야 할 필요성이 있다. 기존의 화질개선방법으로는 Land의 인간의 시각적 모델을 바탕으로 한 Retinex 알고리즘이 대표적이다. Retinex 알고리즘은 칼라의 일관성과 시각적인 개선을 제공하지만, 전역적인 contrast 감소와 후광효과 및 색왜곡 문제를 발생시키기도 한다. 이러한 문제를 개선하기 위해 본 논문에서는 YCbCr 색공간에서 휘도성분의 주파수성분에 대한 처리를 통해 전역적 contrast를 향상시키고, 색차성분에 대한 처리를 통해 칼라 선명도를 향상시키는 방법을 제안한다. 실험 결과영상의 비교를 통해 제안된 알고리즘이 기존의 알고리즘에 비해 연산량 감소효과가 뛰어나며 전역적 contrast 향상과 색상 보전 성능이 우수하고 후광효과를 효과적으로 제거함을 확인하였다.

• 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.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권1호
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• pp.794-797
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• 2007

We have developed the adaptive contrast ratio enhancement algorithm for mobile LCD. This algorithm aims at effective contrast ratio enhancement with minimizing degeneration of color and white balance. It also is very simple to fit mobile LCD system.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.917-918
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• 2008

Histogram Equalization (HE) method is widely used for contrast enhancement. However, HE often introduce washed out appearance or color distortion due to the over enhancement in contrast. In this paper, Dynamic Range Separate Histogram Equalization (DRSHE) is proposed for contrast enhancement. DRSHE reconfigures the dynamic range of histogram using probability distribution ratio. The experimental results show that DRSHE suppresses the washed out appearance or color distortion and preserves naturalness of the original image compared with conventional methods.