• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.651-661
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• 2008

This paper proposes a novel contrast enhancement (CE) algorithm for color images using the modified error diffusion (ED). After conventional color histogram equalization (HE), artifacts such as false contours are produced in the contrast enhanced image. The proposed CE algorithm using the modified ED consists of two parts: CE and ED. In the first part, a low-contrast input image is enhanced by the conventional HE method. In the second part, we use the modified ED algorithm. The inputs of the second part are the average and scaled difference images of the original color input image and the HE image, in which the scaled color difference image is diffused by the ED algorithm. In the proposed algorithm, the modified ED algorithm reduces the artifacts produced in the HE image, and increases the number of color levels. Computer simulations with a number of low-contrast color images show the effectiveness of the proposed CE method in terms of the visual quality as well as the probability mass function. It can be used as a post-processing for CE with simultaneous artifact reduction in various display devices.

• 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.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.119-130
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• 2013

In this paper, we propose a new color image enhancement method to improve the color saturation as well as luminance contrast in the YCbCr color space. The proposed method uses the maximum color difference table to compensate the perceived saturation changes due to luminance contrast changes. To improve the color saturation, the method first calculates the weighting factor by using the maximum color difference table and then multiplies the weighting factor to the input color difference signals. In this step, it maps color difference signals to proper color region to prevent the color distortion by considering the correlation of color saturations depending on the luminance and hue. The experimental results show that our method effectively improves color saturation compared to the conventional methods.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.369-370
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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.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.707-714
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• 2019

Recently, as the sensor network technologies and camera technologies develops, there are increasing needs by combining two technologies to effectively observe or monitor the areas that are difficult for people to access by using the visual sensor network. Since the applications using visual sensors take pictures of the outdoor areas, the images may not be well contrasted due to cloudy weather or low-light time periods such as a sunset. In this paper, we first model the color characteristics according to illumination using the characteristics of visual sensors that continuously capture the same area. Using this model, a new method for improving low contrast images in real time is proposed. In order to make the model, the regions of interest consisting of the same color are set up and the changes of color according to the brightness of images are measured. The gamma function is used to model color characteristics using the measured data. It is shown by experimental results that the proposed method improves the contrast of an image by adjusting the color components of the low contrast image simply and accurately.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.215-218
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• 2013

In this paper, we proposed a method for enhancement of color images with sky regions. The input image is converted into HSV space and then sky and non-sky regions are separated. For sky region, saturation enhancement is performed for each pixel based on the enhancement factor calculated from the average saturation of its local neighborhood. On the other hand, for the non-sky region, the enhancement is applied only on the luminance value (V) component of the HSV color image, which is performed in two steps. The luminance enhancement, which is also called as dynamic range compression, is carried out using nonlinear transfer function. Again, each pixel is further enhanced for the adjustment of the image contrast depending upon the center pixel and its neighborhood pixel values. At last, the original H and V component image and enhanced S component image for the sky region, and original H and S component image and enhanced V component image for the non-sky region are converted back to RGB image.

• Korean Journal of Cognitive Science
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• v.25 no.1
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• pp.51-71
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• 2014

This paper presents an image enhancement method in real road traffic scenes. The images captured by the camera on the car cannot keep the color constancy as illumination or weather changes. In the real environment, these problems are more worse at back light conditions and at night that make more difficult to the applications of the vision-based intelligent vehicles. Using the existing image enhancement methods without considering the position and intensity of the light source and their geometric relations the image quality can even be deteriorated. Thus, this paper presents a fast and effective method for image enhancement resembling human cognitive system which consists of 1) image preprocessing, 2) color-contrast evaluation, 3) alpha blending of over/under estimated image and preprocessed image. An input image is first preprocessed by gamma correction, and then enhanced by an Automatic Color Enhancement(ACE) method. Finally, the preprocessed image and the ACE image are blended to improve image visibility. The proposed method shows drastically enhanced results visually, and improves the performance in traffic sign detection of the vision based intelligent vehicle applications.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.233-239
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• 2016

Color enhancement basically deals with color manipulation in digital images. Recently, the technique has become widely used as a result of the increasing use of digital cameras. Retinex-based colorenhancement algorithms are a popular technique. In this paper, retinex with bilateral filtering is proposed to improve the quality of poorly illuminated images. Generally, it consists of three main steps: first, a retinex-based algorithm with color restoration; second, transformation mapping using histogram matching; and finally, smoothing the image using a bilateral filter. The experimental results demonstrate that the proposed method can successfully enhance image contrast while avoiding the halo effect and maintaining the color distribution in the image.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.103-108
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• 1993

An image can be largely corrupted by the ambient illuminant, so that the image enhancement to restory natural color without respect to the ambient illuminant is needed. It this paper, a new color image enhancement technique based on color constancy is proposed. To enhance the image quality, higher volues of contrast and saturation are preferred, but their excessive values make an image unnatural. Since the color constancy processing preserves only hue, while reducing the dynamic range of lightness and saturation,the technique is needed in order to compensate this phenomenon. The proposed method transforms and increases lightness and saturation simultaneously to avoid the complexity in the related transformation by analyzing the relationship between the RGB and modified IHS coordinate system.

• Journal of Broadcast Engineering
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• v.22 no.5
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• pp.608-617
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• 2017

Methods of contrast enhancement have problem such as side effect of over-enhancement with non-gaussian histogram distribution, tradeoff enhancement efficiency against brightness preserving. In order to enhance contrast at various histogram distribution, segmentation to region with gaussian distribution and then enhance contrast each region. First, we segment an image into several regions using GMM(Gaussian Mixture Model)fitting by that k-mean clustering and EM(Expectation-Maximization) in $L^*a^*b^*$ color space. As a result region segmentation, we get the region map and probability map. Then we apply local contrast enhancement algorithm that mean shift to minimum overlapping of each region and preserve brightness histogram equalization. Experiment result show that proposed region based contrast enhancement method compare to the conventional method as AMBE(AbsoluteMean Brightness Error) and AE(Average Entropy), brightness is maintained and represented detail information.