• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.460-463
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• 2003

본 논문은 프리미티브 모델을 바탕으로 윤곽선 추출하여 효율적으로 홀 채워서 결과 영상의 질과 속도를 향상시키는 알고리즘을 제시한다. 이 알고리즘은 입력 영상에서 뷰의 위치와 방향이 바뀌어 홀이 발생하면 그 홀을 동일 프리미티브의 윤곽선을 이용하여 프리미티브 내의 영상 정보만을 이용하므로 이질감이 작고 홀 주위의 모든 점들의 영상 정보를 이용하여 결과 영상의 질을 향상 시켰다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2664-2669
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• 2011

We proposed a new method to improve the resolution of far object image in curving effective integral imaging system. Basically, the curving effective integral imaging(CEII) system can improve the resolution of the reconstructed images with an increased sampling rate of elemental images. However, in the case when an object located far from the lenslet array is picked up, the low resolution of the reconstructed images of the far object has been a primary problem because the sampling rate is very low. In order to solve this drawback, by using the direct pixel mapping(DPM) method the EIA picked up from a far object is transformed into a new EIA that virtually looks like the EIA picked up from the object originally located close to the lenslet array. From this new EIA, highly resolution-enhanced images of far object could be reconstructed in the CEII system. To show the feasibility of the proposed method, simulation results are compared with the conventional method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.177-180
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• 2003

텔레비젼 카메라, 비디콘 카메라(vidicon camera), 디지털 검지기, 스캐너 등 물리적 장치로 획득한 영상은 주위의 밝기로 인하여 어두운 영상을 얻거나 영상장치의 물리적 속성과 영상 전송에 기인하여 영상은 열악한 대비를 가질 수 있다. 본 논문에서는 획득한 저대비 영상을 대비 향상시켜주는 기법을 제안한다. 제안된 기법은 K-means 알고리듬을 사용하여 교차점을 자동으로 선정하는 방법을 사용한다. 이 최적의 교차점을 선정하는 과정은 획득한 영상을 물체와 배경으로 분리하는 두 개의 클래스 문제로 보고 K-means 알고리듬을 적용하였다. 구한 교차점을 사용하여 영상을 양분하여 히스토그램 평활화 방법을 적용하였다. 본 논문에서는 퍼지성 지수(index of fuzziness)를 사용하여 향상의 정도를 측정하였다. 제안된 기법을 저대비 영상에 적용하였으며 그 결과를 히스토그램 평활화 기법의 결과와 비교하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.777-781
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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 IAFC model is used to classify the image into two classes. The proposed method is applied to several 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.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.104-111
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• 2010

This paper presents an adaptive image enhancement method using the spatial frequency property in the DCT(discrete cosine transform) compressed domain. The dc coefficients, the illumination components of image, are adjusted to compress the dynamic range of image, and the ac coefficients are modified to enhance the contrast by using the human visual system(HVS) and the spatial frequency property. The ac coefficients are separated into vertical direction, horizontal direction, and mixed spatial frequency components, and adaptively modified to minimize the block artifacts that possibly occur in the image enhancement. The proposed method using dynamic range compression and adaptive contrast enhancement shows the advanced performance without the block artifact compared with existing method.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.332-345
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• 2010

A unified image enhancement method is proposed for high-resolution image which based on color constancy and histogram equalization using edge region. To speed up the method, smaller image is used when parameters of color constancy and histogram equalization are determined. In the color constancy process, nth-derivative of gaussian is applied to x and y axis separately in order to estimate the color of the illumination rapidly. In the histogram equalization process, the histogram obtained from near-edge region is used for the histogram equalization. In the experiments, high-resolution images taken by digital camcorder are used for verifying the performance of the proposed method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.533-540
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• 2021

High-resolution satellite images have high potential to acquire geospatial information over inaccessible areas such as Antarctica. Reference data are often required to increase the positional accuracy of the satellite data but the data are not available in many inland areas in Antarctica. Therefore this paper presents a multi-image RPCs (Rational Polynomial Coefficients) sensor modeling without any ground controls or reference data. Conjugate points between multi-images are extracted and used for the multi-image sensor modeling. The experiment was carried out for Kompsat-3A and showed that the significant accuracy increase was not observed but the approach has potential to suppress the maximum errors, especially the vertical errors.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.18-26
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• 2009

Image resolution enhancement algorithm is a basic technique for image enlargement and restoration. The main problem is the image quality degradation such as blurring or blocking effects. In this paper, we propose loss information estimation and image resolution enhancement method using low level interpolation method. In the proposed method, loss information is computed by downsampling -interpolation process of obtained low resolution image. We estimate loss information of high resolution image using interpolation of the computed loss information. Lastly, we add up interpolated high resolution image and the estimated loss information which is applied a weight factor. Our experiments obtained the average PSNR 1.4dB which is improved results better than conventional algorithm. Also subjective image quality is more clearness and distinctness. The proposed method may be helpful for various video applications which required improvement of image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.19-26
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• 2007

In the sigma filter, there is a specialized neighbours distribution scheme in which the sigma value is computed from local statistics. It is designed to modify a standard average filter to preserve edges. However this filter is vulnerable to details-enhancement and conventional sigma approaches have been focused on denoising, not enhancing the characteristic area. This paper proposes an adaptive image enhancement algorithm using local statistics and functional synthesis which are utilized for adaptive realization of the enhancement, so that not only image noise may be smoothed but also details may be enhanced. For the local adaptation, parameters are estimated and weighted at each moving window that satisfy the criteria. The experimental results illuminates the effectiveness of the proposed method.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.770-773
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• 2015

The contrast of the intensity components of color images usually needs to be improved in order to enhance the visual quality of color images. However, pure color regions can be saturated due to the excessive enhancement of that color. In this paper, a new method for enhancing the visual quality of color images using saturation components in the HSI color space is proposed, and the same enhancement technique in the YCbCr color space is proposed. Computer simulations show that the proposed method provides improved visual quality compared to the conventional methods.