• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.141-147
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• 2015

The contrast of a display is generally evaluated by using the ratio of the minimum luminance to the maximum luminance of the display. However, this contrast ratio is not matched with perceived contrast because it uses only physical characteristic of display without considering human perceptual characteristics. In this paper, the proposed contrast measure that considers perceptually discriminable brightness within the range of display brightness is suggested. First, the range between the minimum and maximum brightness of display in CIECAM02 color space is calculated to measure the length of perceived brightness for the display. Next, brightness ranges which are perceptually same at each brightness level are determined by applying Weber-Fechner ratio and then, the number of brightness values within each brightness range is counted. Finally, perceptually discriminable brightness is defined as the sum of ratio between the number of brightness values in each brightness range and the perceptual contrast length of the display. In the experiments, preference test using various displays with random brightness patches is performed to evaluate perceived contrast. As a result, the proposed measure is more consistent with human perception than the previous contrast measures.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.11a
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• pp.70-73
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• 1998

영상 디스플레이에서 Brigtness와 Contrast의 조전상태는 영상색에 지대한 영향을 미친다. 본 연구에서는 최적의 Contrst와 Contrast 상태를 손쉽게 조절할 수 있는 패턴을 고안하였으며 Brightness/Contrast 통합 조절방법을 제시하여 주변 조명이나 개인의 감성에 따른 영상색의 쉽고 다양한 조정을 가능하게 하여 사용자의 편의성을 높였다.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.373-374
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• 2007

This paper proposes a natural contrast enhancement algorithm that preserves the brightness of an image. In the case that an image has the partially dense distribution of intensity, conventional contrast enhancement algorithms degrade the image quality because they excessively change the intensity values. In contrast to convention algorithms, the proposed method is able to obtain a natural image with the high contrast using the concept of brightness preservation. The experimental results show the effectiveness of our algorithm.

• Science of Emotion and Sensibility
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• v.2 no.1
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• pp.113-119
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• 1999

brightness와 contrast의 적절한 조절은 자연색 재현 및 다양한 분위기 창출이 가능하여 디스플레이의 질을 향상시킬 수 있다. 디스플레이 사용자들은 OSD(On-Screen-Display)를 통해 brightness와 contrast상태를 임의로 조절할 수 있으나, 조절에 따른 영상의 변화를 예측하지 못하므로 이를 잘 활용하지 못하고 있다. 본 연구에서는 brightness와 contrast가 각각 영상에 미치는 영향을 분석하여 자연색 재현이 가능한 최적상태와 4가지의 감성적 분위기를 나타낼 수 있는 조절상태를 정의하였다. 5가지 조절상태를 OSD에 제시함으로써 사용자가 쉽게 영상의 이미지에 적합한 brightness와 contrast상태로 조절할 수 있어 제품에 대한 만족감을 높일 수 있는 brightness/contrast 통함 조절방법을 제안하였다.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.1
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• pp.14-21
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• 2008

In this paper, we propose an adaptive contrast enhancement method using dynamic range segmentation. Histogram Equalization (HE) method is widely used for contrast enhancement. However, histogram equalization method is not suitable for commercial display because it may cause undesirable artifacts due to the significant change in brightness. The proposed algorithm segments the dynamic range of the histogram and redistributes the pixel intensities by the segment area ratio. The proposed method may cause over compressed effect when intensity distribution of an original image is concentrated in specific narrow region. In order to overcome this problem, we introduce an adaptive scale factor. The experimental results show that the proposed algorithm suppresses the significant change in brightness and provides wide histogram distribution compared with histogram equalization.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2403-2406
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• 2003

When viewing images, the relative luminance of the surround has a profound impact on the apparent contrast of the image. The dark surround causes the image elements to appear lighter than those viewed in an illuminated surround. For this reason, it is worthwhile to briefly review the general results of brightness sealing under a various viewing condition. Two of the most often cited parers on the topic of brightness scaling are Stevens-stevens and Bartleson-Breneman's function. There are, however, significant differences between the perceptual functions for simple-field and complex-field viewing. In this paper, we research the relationship between Steven's power law and Bartleson-Breneman's function. We present an appropriate brightness perception function due to TV system viewing conditions. Highlight luminance peak and absolute brightness threshold value in various adaptation levels are obtained from the proposed brightness function . Also, the luminance value of black level to produce the same contrast ratio with variety of display highlight luminance peak is obtained from the proposed brightness function.

• Journal of the Optical Society of Korea
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• v.18 no.1
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• pp.89-94
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• 2014

It is established that the perceived image contrast is affected by surround luminance. In order to get the same perceived image contrast, the optimum surround compensation ratios for those surround conditions is needed. Much research has been performed for dark, dim, and average surrounds. In this study, a wide range of surround luminance from dark up to $2087cd/m^2$ was considered. Using magnitude estimation method, the change in perceived brightness of six test stimuli was measured under seven surround conditions; dark, dim, 2 levels of average, bright, and 2 levels of over-bright surrounds. To drive the perceived image contrast from the perceived brightness, two different definitions of contrast were tested. Their calculated results were compared with the visual data of our previous work. And to conclude, the perceived contrast compensation ratios were 1:1.11:1.2 for average, dim and dark surrounds. These were close to CIECAM02 model (1:1.17:1.31). Besides, for average, bright, over-bright1 and over-bright2 surrounds the ratios 1:1.17:1.42:1.69 were determined. For intermediate or more extreme surround conditions, the compensation ratio was obtained from the linear interpolation or extrapolation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.388-393
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• 2012

Acoustic brightness and contrast control are promising techniques for manipulating acoustic energy over selected zones of interest using loudspeaker arrays. In this paper, the fundamental theory and concept of the brightness and contrast control is reviewed. The similarity and difference of two different strategies are explained in terms of the constraint required to determine a unique solution among many possible candidates. The application examples and recent progresses of the brightness and contrast control are presented.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.59-62
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• 2018

In this paper, we propose a contrast enhancement algorithm using guided image filter (GIF). The GIF is used to divide an HDR image into a base layer and a detail layer. The energy scale of base layer determinate the darkness and brightness of the image. However, the detail information in the base layer is difficult to be displayed because of the high brightness and clusters of low brightness. We propose a contrast enhancement method by adjusting the gray level of base layer by subtracting the mean value of itself. It is combined with the detail layer to preserve the detail information. Experiment results show that the proposed algorithm has better performance in detail preservation and contrast enhancement.

• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.453-467
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• 2014

A typical histogram equalization contrast enhancement effect for improving the image quality is excellent. However, because it appears that excessive changes of the brightness values, The average brightness of the image is changing in units of frames of applications such as a TV video is unsuitable. In order to solve these drawbacks, a modified method of histogram equalization on various studies have been made. But the result images of existing methods sometimes shown visual degradations such as over-enhancement and false contouring. In this paper, we propose improved contrast enhancement method through bi-histogram equalization using target mean brightness based on differential compression method. The proposed method is based on the average brightness value by dividing the histogram, the histogram for each zone, according to the frequency differential of compression. And equalize the modified histogram based on target mean brightness. This allows to suppress deterioration of picture quality, and changes in the average brightness of each frame of video, while maintaining and improving the contrast. Experimental results show that the proposed method compared to the conventional method, the average brightness of each frame from a movie well maintained, and no degradation of the image quality showed a good effect to improve the contrast.