• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1160-1163
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• 2009

Many researches showed that perceived image contrast increases as the relative surround luminance increases. However, most experiments were conducted under limited surround conditions. In this research, a psychophysical experiment was conducted to investigate the change in perceived image contrast under wide range of surround luminance up to 1820 cd/$m^2$. A large area illuminator was used as a backlight. It consists of 23 dimmable fluorescent lamps and a sheet of diffuser. The luminance could be adjusted to 7 different surround ratios: 0, 0.3, 0.56, 0.96, 2.24, 5.81, and 9.99. Results showed that perceived image contrast changes as a typical band-pass shape and the maximum contrast is found near $S_R$=1.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.972-974
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• 2009

This paper presents smart regional contrast enhancement technique of partitioned image for local dimming backlight on small-sized mobile display to reach two goals. One is to save the power consumption, and the other to improve contrast ratio of display image. Recently new advanced method is proposed, named local dimming method, that backlight LED is positioned on backside of the display panel. So it is important to partition an image by sub blocks and then post-processing independantly. This means regional contrast enhancement. After partitioning, we compare the mean luminance(Y) value of each sub-block image with the one of original whole image. If some blocks have the mean value lower than the one of whole image, they are processed with the proposed method and others are bypassed. Simultaneously the information of the processed blocks are transferred to BLC(Backlight LED Controller). And then the supply current of each backlight LED is reduced to realize the contrast ratio enhancement and at the same time to power consumption reduction. In addition, we verify this proposed method is free from blocking artifacts.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.176-178
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• 2016

Single image를 사용하여 안개양을 측정하는 방법으로는 소실점, 지평선의 local contrast를 측정하는 방법과 DCP의 빛 전 달양을 사용하는 방법이 있다. 하지만 local contrast를 사용하는 방법은 특정한 환경에서만 사용이 가능하고 DCP는 대기의 color와 비슷한 color를 가진 물체들이 많을 경우 사용하기 어렵다는 한계가 있다. 그래서 본 논문은 영상의 빛 전달양과 Local Contrast를 사용하여 다양한 contents를 가진 single image에서 안개양을 수치화하는 새로운 방법을 제시한다. 제시하는 방법은 DCP로부터 측정한 빛 전달량으로부터 안개일 가능성이 있는 빛 전달량 지역의 면적과 해당 지역에서의 Local contrast의 분포 정도를 측정하여 DoF를 계산한다.

• Journal of the Korea Society of Computer and Information
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• v.22 no.1
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• pp.9-14
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• 2017

In this paper, we propose that the contrast features of octave spectrum can be used to show spectral contrast features of some music clips. It shows the relative spectral distribution rather than average spectrum. From the experiment, it can be seen the method of spectral contrast features has a good performance in classification of music styles. Another comparative experiment shows that the method of spectral contrast features can better distinguish different music styles than the method of MFCC features that commonly used previously in the classification system of music styles.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.361-362
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• 2007

We propose a contrast-controlled feature detection approach for steel radiograph image. X-ray images are low contrast, dark and high noise image. So, It is not simple to detect defects directly in automated radiography inspection system. Contrast enhancement, histogram equalization and median filter are the most frequently used techniques to enhance the X-ray images. In this paper, the adaptive control method based on contrast limited histogram equalization is compared with several histogram techniques. Through comparative analysis, CLAHE(contrast controlled adaptive histogram equalization) can enhance detection of defects better.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.295-299
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• 2002

This paper presents an image contrast enhancement technique for improving low contrast images. We applied fuzzy logic to develop an image contrast enhancement technique in the viewpoint of considering that the low pictorial information of a low contrast image is due to the vaguness or fuzziness of the multivalued levels of brightness rather than randomness. The fuzzy image contrast enhancement technique consists of three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. In the stage of image fuzzification, we need to select a crossover point. To select the crossover point automatically the K-means algorithm is used. The problem of crossover point selection can be considered as the two-category, object and background, classification problem. The proposed method is applied to an experimental image with 256 gray levels and the result of the proposed method is compared with that of the histogram equalization technique. We used the index of fuzziness as a measure of image quality. The result shows that the proposed method is better than the histogram equalization technique.

• Journal of Information Display
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• v.12 no.2
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• pp.85-87
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• 2011

The contrast ratio is one of the most important performance parameters for display devices. The general method of measuring the contrast ratio is to determine the ratio of the full-screen white pattern to the full-screen black pattern, according to the Video Electronics Standards Association standard. Real TV images seldom have these images, however, and the conventional method does not reflect the true performance of the display in actual use. In this paper, a new contrast ratio measurement method that uses image patterns is proposed, to demonstrate that active matrix organic light-emitting diode TVs have a higher contrast than LED (LCD) TVs.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.41-52
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• 2018

This paper presents a method for accurate camera self-calibration based on SIFT Feature Detection and image quality assessment. We performed image quality assessment to select high quality images for the camera self-calibration process. We defined high quality images as those that contain little or no blur, and have maximum contrast among images captured within a short period. The image quality assessment includes blur detection and contrast assessment. Blur detection is based on the statistical analysis of energy and standard deviation of high frequency components of the images using Discrete Cosine Transform. Contrast assessment is based on contrast measurement and selection of the high contrast images among some images captured in a short period. Experimental results show little or no distortion in the perspective view of the images. Thus, the suggested method achieves camera self-calibration accuracy of approximately 93%.

• Korean Journal of Veterinary Research
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• v.51 no.2
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• pp.165-169
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• 2011

Barium suspension, oral iodine contrast medium and water were applied in eight dogs to evaluate (1) distension of gastrointestinal tract, (2) the effect of the oral contrast media on the identification of the pancreas from surrounding organs, and (3) image quality and the presence of artifacts in canine pancreas computed tomography (CT) images. Oral iodine contrast medium, gastrografin, produced significant artifacts that deteriorated the CT images of the pancreas. The use of water did not provide the fullness of the gastrointestinal lumens. Barium suspension was effective for the identification of the pancreas from the surrounding gastrointestinal tract, without significantly increasing image noise. Barium suspension can be used as an optimal contrast medium that will not cause an adverse effect on the pancreatic density and image quality.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.808-810
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• 2004

본 논문에서는 Contrast map과 Salient point를 이용하여 영상에서 중요한 객체를 자동으로 추출하는 방법을 제안한다. 우선 인간의 시각 체계와 유사한 밝기(luminance), 색상(color) 그리고 방향성(orientation) 3가지의 특징정보를 이용하여 각각의 특징정보로부터 feature map을 생성하고 이 3가지의 feature map을 선형 결합하여 contrast map을 생성한다. 이렇게 생성된 하나의 contrast map을 이용하여 대략적인 Attention Window (AW)의 위치를 결정한다. 다음으로, 영상으로부터 웨이블릿 변환을 적용하여 salient point를 찾고, salient point의 분포와 contrast map의 중요도에 따라 AW의 크기를 실제 중요 객체의 크기와 가장 유사하도록 축소시킨다. 이렇게 선택되고 축소된 AW안에서 실제 중요 객체를 추출하기 위해 AW 내부에 존재하는 영상에 대해서만 영상 분할을 하고 불필요한 영역을 제거하여 자동으로 중요객체를 추출하도록 한다.