• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.119-130
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• 2013

In this paper, we propose a new color image enhancement method to improve the color saturation as well as luminance contrast in the YCbCr color space. The proposed method uses the maximum color difference table to compensate the perceived saturation changes due to luminance contrast changes. To improve the color saturation, the method first calculates the weighting factor by using the maximum color difference table and then multiplies the weighting factor to the input color difference signals. In this step, it maps color difference signals to proper color region to prevent the color distortion by considering the correlation of color saturations depending on the luminance and hue. The experimental results show that our method effectively improves color saturation compared to the conventional methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.658-665
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• 2015

In the production of medical images, noise reduction and contrast enhancement are important methods to increase qualities of processing results. By using the edge-based denoising and adaptive nonlinear histogram stretching, a novel medical image enhancement algorithm is proposed. First, a medical image is decomposed by wavelet transform, and then all high frequency sub-images are decomposed by Haar transform. At the same time, edge detection with Sobel operator is performed. Second, noises in all high frequency sub-images are reduced by edge-based soft-threshold method. Third, high frequency coefficients are further enhanced by adaptive weight values in different sub-images. Finally, an adaptive nonlinear histogram stretching method is applied to increase the contrast of resultant image. Experimental results show that the proposed algorithm can enhance a low contrast medical image while preserving edges effectively without blurring the details.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.181-184
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• 2009

본 논문은 번호판 내 명암도 대비를 이용한 자동차 번호판 검출 기법을 제안한다. 평균값 필터와 라플라시안 필터를 사용하여 영상의 잡음을 제거하는 동시에 에지 성분을 향상시킨 후 조명 환경 변화에 강인한 번호판 내 명암도 대비 특징을 이용하여 문자 후보를 검출한다. 다음으로 검출된 문자 후보가 열을 이루는 텍스트 후보를 검출하고, 이 영역을 Otsu 이진화 기업을 사용하여 x축에 투영하였을 시 나타나는 패턴을 평가함으로써 최종적으로 자동차 번호판을 검출하게 된다. 제안하는 기법의 성능을 평가하기 위해 다수의 데이터를 사용하여 실험하였고, 이를 분석하여 제안하는 기법의 우수성을 검증하였다.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.462-470
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• 2008

This study applies fuzzy functions to improve image quality under the assumption that uncertainty of image information due to low contrast is based on vagueness and ambiguity of the brightness pixel values. To solve the problem of low contrast images whose brightness distribution is inclined, we use the k-means algorithm as a parameter of the fuzzy function, through which automatic critical points can be found to differentiate objects from background and contrast between bright and dark points can be improved. The fuzzy function is presented at the three main stages presented to improve image quality: fuzzification, contrast enhancement and defuzzification. To measure improved image quality, we present the fuzzy index and entropy index and in comparison with those of histogram equalization technique, it shows outstanding performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.527-530
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• 2001

영상이 시각적인 해석을 위해 처리될 때, 퍼지 이론이 영상 대비 강화에 많이 사용되고 있다. 적응적 퍼지 클러스터링 기법을 사용하여 자동적으로 영상의 명암도에 대한 다중 클래스를 형성하고 여기에 각각의 명암도를 속성 공간으로 전환시키는 퍼지함수를 사용하여 각 픽셀의 명암도에 부합하는 퍼지 소속도를 구한다. 영상 대비 향상을 위하여 구한 퍼지 소속도에 강화 연산자를 반복적 적용한다. 본 논문에서 제안한 방법을 히스토그램 평활화와 비교하기 위해 흑백 영상에 적용하였다.

• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.453-467
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• 2014

A typical histogram equalization contrast enhancement effect for improving the image quality is excellent. However, because it appears that excessive changes of the brightness values, The average brightness of the image is changing in units of frames of applications such as a TV video is unsuitable. In order to solve these drawbacks, a modified method of histogram equalization on various studies have been made. But the result images of existing methods sometimes shown visual degradations such as over-enhancement and false contouring. In this paper, we propose improved contrast enhancement method through bi-histogram equalization using target mean brightness based on differential compression method. The proposed method is based on the average brightness value by dividing the histogram, the histogram for each zone, according to the frequency differential of compression. And equalize the modified histogram based on target mean brightness. This allows to suppress deterioration of picture quality, and changes in the average brightness of each frame of video, while maintaining and improving the contrast. Experimental results show that the proposed method compared to the conventional method, the average brightness of each frame from a movie well maintained, and no degradation of the image quality showed a good effect to improve the contrast.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.59-62
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• 2021

본 논문에서는 사다리꼴 형태의 소속 함수를 적용하여 스트레칭 하는 과정에서 상한과 하한을 FCM 기반 양자화 기법을 적용하여 동적으로 조정하는 퍼지 스트레칭 기법을 제안한다. 제안된 퍼지 스트레칭 기법은 FCM 기반 양자화 기법을 적용하여 각 클러스터를 생성하고 생성된 각 클러스터의 중심에 해당되는 명암도를 이용하여 사다리꼴 형태의 소속 함수의 구간을 설정한다. 그리고 설정한 구간 정보를 이용하여 스트레칭을 위한 상한과 하한을 구하여 영상을 스트레칭 한다. 제안된 FCM 양자화 기반 퍼지 스트레칭 기법의 성능을 분석하기 위해서 명암도 분포가 좁고 명암 대비가 낮은 결절종 초음파 영상과 컨테이너 영상을 대상으로 실험하였다. 실험 결과에서도 알 수 있듯이 기존의 히스토그램 스트레칭 기법과 삼각형 형태의 소속 함수를 적용한 퍼지 스트레칭 기법보다 명암 대비가 향상되었다. 결절종 초음파 영상에서는 결절종 영역과 그 외의 영역 간의 명암 대비가 뚜렷하게 나타나서 결절종 추출에 효과적인 것을 확인하였고 컨테이너 영상에서는 컨테이너 데미지를 추출하는데 필요한 컨테이너 굴곡선 등과 같은 특징이 다른 기법들에 비해 선명하게 나타났다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.1
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• pp.10-21
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• 2009

In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes those regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrast in the images and the results are compared to the conventional approaches to show its superiority.

• 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 Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.32-39
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• 2012

This paper develops a robust image enhancement method by adjusting image signal energy according to the direction and the variation of image signal in DCT domain. To accomplish this, we measure the gradient of image signal directly in DCT domain and then adjust frequency components involved in sharpness, local contrast and global contrast using the direction and the magnitude of the measured gradient The experiment showed that the proposed method produces the best quality of an image without causing blocking, ringing artifacts and boosting noise.