• Cartoon and Animation Studies
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• s.15
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• pp.73-88
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• 2009

Light is a basic force that functions in all the formative arts. Light (brightness) is an important subject of study in that it contains the force to control emotion and has much influence upon the shaping of a visual image and a feeling. If an artist systematizes the characteristics of brightness and creates an image, he or she can acquire a useful tool of expression. Because light is a powerful medium of expression of a visual image, a study on the characteristics of brightness for the emotional expression of an image in the contextual relationship with narratives seemingly has a crucial meaning. Emotion is influenced by a visual image very much, and a visual image is inevitably influenced by light. The brightness by light is basically classified into bright, dim, and dark. And the three basic stages of brightness specialize an image according to the setting of scope of maximal and minimal luminosity, and the image is further differentiated by the size of bright portion or dark portion. Since emotion is such a phenomenon as immaterial and psychological, it is difficult to break down it. Furthermore, clarifying the principle of an image in which the shade of light is associated is impossible. However, the width of luminosity and the change of size can give quite a change to a visual image, and the visual image has further influence upon man's emotion too. Although the influence of brightness upon a visual image varies with extents, circumstances, and personal tastes and interests, even the same image clearly changes with the adjustment of brightness.

• Journal of Biomedical Engineering Research
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• v.23 no.4
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• pp.263-268
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• 2002

The image quality of imageguide depends on the structure, material, length of microfibers and the phenomena such as cross-talk and leaky ray between adjacent fibers. These Parameters should be considered as important factors in the image transmission qualify of fibers. However it is considered to be very difficult to assess all the parameters in a consistent way Therefore. two image characteristics, image resolution and image brightness are measured and analyzed to determine the image quality of imageguide. But the exact methods to measure two image characteristics of imageguide are not reported. In this study, the image brightness of imageguide for ultrathin endoscope is determined by measuring of the numerical aperture. the packing fraction and the attenuated power ratio of imageguide. Especially it is possible to obtain more exact results from measuring the numerical aperture of whole image guide than those from theoretical calculation of the single microfiber in an image guide. The image brightness of the image guide which has $3.1\mu m$ microfibers is about 37% less than that with $4.1\mu m$ microfibers.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.77-86
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• 2014

Mobile devices are generally using app images which are artificially designed. Accordingly, this paper presents adjusting device brightness based on app image categorization for enhancing the visibility under various light condition. First, the proposed method performed two prior subjective tests under various lighting conditions for selecting features of app images concerning visibility and for selecting satisfactory range of device brightness for each app image. Then, the relationship between selected features of app image and satisfactory range of device brightness is analyzed. Next, app images are categorized by using two features of average brightness of app image and distribution ratio of advanced colors that are related to satisfaction range of device brightness. Then, optimal device brightness for each category is selected by having the maximum frequency of satisfaction device brightness. Experimental results show that the categorized app images with optimal device brightness have high satisfaction ratio under various light conditions.

• Journal of the Semiconductor & Display Technology
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• v.8 no.4
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• pp.95-100
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• 2009

This paper presents an efficient disparity matching, using sum of absolute difference (SAD) and dynamic programming (DP) algorithm. This algorithm makes use of one of area-based algorithm which is the absolute sum of the pixel difference corresponding to the window size. We use the information of the right eye brightness (B) and the left eye brightness to get an best matching results and apply the results to the left eye image using the window go by the brightness of the right eye image. This is that we can control the brightness. The major feature of this algorithm called SAD+DP+B is that although Root Mean Square (RMS) performance is slightly less than SAD+DP, due to comparing original image, its visual performance is increased drastically for matching the disparity map on account of its matching compared to SAD+DP. The simulation results demonstrate that the visual performance can be increased and the RMS is competitive with or slightly higher than SAD+DP.

• 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.

• International Journal of Advanced Culture Technology
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• v.3 no.2
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• pp.161-170
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• 2015

Mean separated histogram equalization in order to preserve the original mean brightness has been proposed. To provide the minimum mean brightness error after the histogram modification, the input image's histogram is successively divided by the factor of 2 until the mean brightness error is satisfied the defined threshold. Then each divided group or sub-histogram will be independently equalized based on the proportional input mean. To provide the overall minimum mean brightness error, each group will be controlled by adding some certain pixels from the adjacent grey level of the next group for giving its mean near by the corresponding the divided mean. However, it still exists some little error which will be put into the next adjacent group. By successive dividing the original histogram, we found that the absolute mean brightness error is gradually decreased when the number of group is increased. Therefore, the error threshold is assigned in order to automatically dividing the original histogram for obtaining the desired absolute mean brightness error (AMBE). This process will be applied to the color image by treating each color independently.

• 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.

• 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 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.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.842-913
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• 1991

The automatic target detection which automatically identifies the location of the target with its input image is one of the significant subjects of image processing field. Then, there are some problems that should be solved to detect the target automatically from the input image. First of all, the ambiguity of the boundary between targets or between a target and background should be solved and the target should be searched adaptively. In other words, the target should be identified by the relative brightness to the background, not by the absolute brightness. In this paper, to solve these problems, a new algorithm which can identify the target automatically is proposed. This algorithm uses the set of fuzzy for solving the ambiguity between the boundaries, and using the weight according to the brightness of data in the input image, the target is identified adaptively by the relative brightness to the background. Applying this algorithm to real images, it is experimentally proved that it is can be effectively applied to the automatic target detection.