• 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.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1291-1296
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• 2005

In this paper, we prevent a display quality drop for image of characteristics brightness ununiformity depend on LED use to LED vision. It is about that method also a control system development equipped with brightness compensation function of LED vision which is done easily for LED set up of LED vision. Generally, It is calculate driving current value is attended by each brightness to brightness characteristics mathematical function establish by "Y=aX+b", When is doing brightness value for "Y", driving current value for "X", brightness compensation value by using time for "b", characteristics value for "a" ground with characteristics curve of LED. So much, First It is create brightness data of each pixel take a photograph red, green and blue of LED vision. Second It is get average error about each pixel which get average brightness value of entire. Last, It is handle a complicated for about gradationally regulation to color and brightness of image send to LED vision. Also It raise the whole average brightness value of vision adjust for "b" value to solve brightness drop problem of LED using the long time.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.283-292
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• 2018

Devices capable of capturing and displaying high dynamic range (HDR) images with significantly increased brightness range compared to low dynamic range (LDR) images have been developed and various methods for efficiently converting the brightness range of an image have been developed. In this paper, we propose a reverse tone mapping method using a guided filter to efficiently convert LDR images into HDR images. After obtaining brightness enhancement function (BEF) using a guided filter, we can reconstruct HDR image from one LDR image. In addition, when the image is too bright or dark, the proposed method maximizes the image quality of the reconstructed HDR image by estimating and adjusting the exposure value before expanding the brightness range of images. Computer simulations show that the proposed method produces HDR images of superior quality compared with the conventional methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.787-789
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• 2017

Edge detection is used in many applications such as image analysis, pattern recognition and computer vision. Existing edge detection methods, there is such Sobel, Prewitt, Roberts, and LoG(Laplacian of Gaussian). In the conventional edge detection method, edge detection is insufficient because the change of the pixel brightness is small when the original image is in low illumination. Therefore, in this paper, we proposed a function to convert the pixel brightness of low illumination image to solve this problem. And it was compared by applying the conventional methods Sobel, Prewitt, Roberts, LoG(Laplacian of Gaussian) to determine the performance of the pixel brightness transform function.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1680-1686
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• 2015

Edge detection is an essential preprocessing for most image processing application, and there are several existing detection methods such as Sobel, Roberts, Laplacian, LoG(Laplacian of Gaussian) operators, etc. Those existing edge detection methods have not given satisfactory results since they do not offer enough pixel brightness change in low light level environment. Therefore, in this study new algorithms using brightness transfer function in the preprocessing and for edge detection applying standard deviation and average-weighted local masks are proposed. In addition, the performance of proposed algorithms was evaluated in comparison with the existing edge detection methods such as Sobel, Roberts, Prewitt, Laplacian, LoG operators.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.836-841
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• 2004

This paper describes ASIC design for brightness revision control, A LED Pixel Matrix (LPM) design and LPM in natural color LED vision. A designed chip has 256 levels of gradation correspond to each Red, Green, Blue LED pixel respectively, which have received 8bit image data. In order to maintain color uniformity by reducing the original rank error of LED, we adjusted the specific character value 'a' and brightness revision value 'b' to pixel unit, module unit and LED vision respectively by brightness characteristic function with 'Y=aX+b'. In this paper, if designed custom chip and brightness revision control method are applied to manufacturing of natural color LED vision, we can obtain good quality of image. Furthermore, it may decrease the cost for manufacturing LED vision or installing the plants.

• ETRI Journal
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• v.39 no.1
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• pp.76-86
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• 2017

In this study, we propose an automatic contrast enhancement method based on transfer function modification (TFM) by histogram equalization. Previous histogram-based global contrast enhancement techniques employ histogram modification, whereas we propose a direct TFM technique that considers the mean brightness of an image during contrast enhancement. The mean point shifting method using a transfer function is proposed to preserve the mean brightness of an image. In addition, the linearization of transfer function technique, which has a histogram flattening effect, is designed to reduce visual artifacts. An attenuation factor is automatically determined using the maximum value of the probability density function in an image to control its rate of contrast. A new quantitative measurement method called sparsity of a histogram is proposed to obtain a better objective comparison relative to previous global contrast enhancement methods. According to our experimental results, we demonstrated the performance of our proposed method based on generalized measures and the newly proposed measurement.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.382-388
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• 2016

When Flat Panel Display (FPD) is made with backlight module, such as LED TV, it inherently suffers from the non-uniform backlight luminance problem that results in un-even brightness distribution throughout the TV screen. If the luminance of each pixel location of a TV screen as a function of the driving voltage can be measured, it can be used to compensate the non-uniformity of the backlight module. We use a carefully calibrated imaging system to take pictures of a TV screen at different levels of brightness and generate the compensation functions for the driving circuitry to correct the luminance level at each pixel location. Making use of the fact that the luminance of the screen is normally brightest at around the center of the screen and gradually decreases toward the border of the screen, the luminance of the whole TV screen is approximated by a mathematical function of the pixel locations. The parameters of the function are computed in the least square sense by the values of both the pixel luminance sent from the driving circuit and the grayscale value measured from the image taken by the imaging system. To justify the correction system, a simple second order polynomial function is used to approximate the luminance across the screen. When the driving circuit voltage is corrected according to the measured function, the variance of the screen luminance is reduced to one tenth of the one measured from the un-corrected TV screen.

• 전자공학회논문지 IE
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• v.46 no.3
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• pp.12-18
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• 2009

In this paper, we developed white balance correction processor for Full Color LED Display System which could be display uniformity color and soft light by adjusting brightness of red, green, blue pixel, individually. This processor correct brightness by calculating operating current of each pixel(red, green, blue LED) on the basis of characteristic curve of LED device when we named "a" as a specific characteristic value, "b" as a brightness correction value according to using time, "X" as a operating current value, and "Y" as brightness value. As the results, we solved the reduction problem of brightness for long used LED devices, according to increase entire mean of brightness value by adjusting "b" value from the brightness characteristic function.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.243-246
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• 2004

In this paper, we have proposed the contrast control method using brightness preserving on the FPD(Flat Panel Display). The proposed algorithms consist of three blocks: the contrast enhancement, the white-level-expander, and the black-level-expander. The proposed method has employed probability density function in order to control the brightness of the image changed extremely. In order for real-time processing, we have calculated cumulative density function using the linear approximation method. The image histogram and image quality were compared with the conventional image enhancement algorithms. The proposed methods have been used in display devices that need image enhancement such as LCD TV, PDP, and FPD.