• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.1
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• pp.22-29
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• 2008

In this paper, we propose an adaptive color enhancement algorithm. It is used for the flat panel displays (FPDs) such as LCD, PDP, and so on. The proposed algorithm consists of an adaptive linear approximation CDF(Cumulative Density Function) algorithm and an adaptive saturation enhancement algorithm. The one is for contrast enhancement which prevents an image from the distortion by luminance transient of an input image. The other is the algorithm which improves the saturation without the contour artifact and over-saturation, whose problems are generated during the enhancing saturation. In addition, it allows to achieve the high quality image using the saturation enhancement method for a preferred color of original image. Visual test and standard deviation of their histograms have been applied to evaluate the resultant output images of the proposed algorithm.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.311-317
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• 2001

The study on Shilla monumental inscription has beer accomplished by many historians. However, the research on enhancement of monumental inscription image using digital image processing technique is not sufficient. The preprocessing using computer is needed fur accurate interpretation of history. In this paper, digital image enhancement algorithm based on mathematical morphology for noise reduction and character clearness is proposed. In the experiment, the subjective image quality is improved using the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2398-2405
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• 2007

This paper proposes a contrast enhancement technique which stretches the intensity surfaces of image to improve the quality of the digital photos. The proposed method enhances the contrast of image by stretching the intensity surface of the original image to the maximum range of the output image in proportion to the distances between the original intensity surface and upper, lower intensity surface, respectively. The upper and lower intensity surfaces are generated from the original intensity surface by gaussian smoothing. In the experiments, digital color images in a variety of illumination conditions were used and the proposed method was compared with other several existed image enhancement algorithms, which are histogram stretching, surface stretching, histogram equalization, gamma correction and retinex. It was proved that the experimental results were more natural visually without deterioration of gradation.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.57-66
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• 2017

Emotional image quality optimization methodologies are investigated using technological image quality controls based on the eye tests of various image samples. The images are evaluated based on various contrast, lightness and saturation image quality metric tone curves. The order of importance to image quality enhancements is contrast, saturation and brightness. The slopes of emotional image qualities with respect to technical image quality metric changes are found to be composed of mathematical function modelling with nearly zero, intermediate and maximum slope regions in general, which can reflect well known log and saturated as well as conventional reverse U shape natures. Image quality improvements are analyzed not only with just single but also with multiple image quality metrics. To ease the unified image quality metric analysis and control, a new function is presented to utilize both the newly found and conventional emotional image quality behaviors. It is found that the overall image quality enhancement can be realized only in a few limited cases of multiple image quality metric controls. It is also found that the kinds of image quality enhancement methodologies are not strongly dependent on image contents (genre).

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.26-31
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• 2016

In this paper, we propose an image quality evaluation system for compact camera module and assess the effect of optical performance improvement for proposed anti-halation disk in small lens. We develop a image quality evaluation system for quality estimation of camera module image. And we also develop a program to control register in image signal processor. Finally the resolution, brightness, and color reproduction performances were evaluated image quality comparison between conventional and proposed camera module using developed quality evaluation system and ISP register control program.

• 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.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1692-1695
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• 2007

We describe the image enhancement method of applying two spatial filters with different characteristics adaptively. An adaptive method is introduced so that sharpness enhancement is performed only in regions where the image exhibits significant dynamics, while noise reduction is achieved in smooth regions. Simulation results show that the proposed method improved the image quality.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.279-282
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• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) Model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved MEC can classify the image into two classes with unsupervised teaming rule. The proposed method is applied to some experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.3
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• pp.130-139
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• 2013

This paper proposes a new approach for enhancing digital images based on red channel information, which has the most analogous characteristics to invisible infrared rays. Specifically, a red channel in RGB space is used to analyze the image contents and improve the visual quality of the input images but it can cause unexpected problems, such as the over-enhancement of reddish input images. To resolve this problem, inter-channel correlations between the color channels were derived, and the weighting parameters for visually pleasant image fusion were estimated. Applying the parameters resulted in significant brightness as well as improvement in the dark and bright regions. Furthermore, simple contrast and color corrections were used to maintain the original contrast level and color tone. The main advantages of the proposed algorithm are 1) it can improve a given image considerably with a simple inter-channel correlation, 2) it can obtain a similar effect of using an extra infrared image, and 3) it is faster than other algorithms compared without artifacts including halo effects. The experimental results showed that the proposed approach could produce better natural images than the existing enhancement algorithms. Therefore, the proposed scheme can be a useful tool for improving the image quality in consumer imaging devices, such as compact cameras.