• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1117-1124
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• 2018

Contrast enhancement plays an important role in various computer vision systems, since their usability can be improved with visibility enhancement of the images affected by weather and lighting conditions. This paper introduces a histogram modification algorithm that reflects the properties of original images in order to eliminate the saturation effect and washed-out of image details due to the over-enhancement. Our method modifies the original histogram so that an additive term fill histogram pits and the gamma correction suppresses histogram spikes. The parameters for the additive term and gamma correction are adjusted automatically according to statistical properties of the images. Experimental results for various low contrast and hazy images demonstrate that the proposed contrast enhancement improves visibility and reduces haze components effectively, while preserving the characteristics of original images, than the conventional methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.963-965
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• 2021

본 논문에서는 위성 영상과 같은 원격 센싱 영상 등의 저 대비 영상의 화질을 개선하기 위하여 SVD (singular value decomposition)를 이용한 적응적 히스토그램 평활화 기법을 제안한다. 저 대비 영상의 특이값과 히스토그램 평활화 영상의 특이값을 결합하되, 사용자 파라미터를 통해 영상의 화질을 조절할 수 있도록 적응적 화질 개선 기법을 제안한다. 위성 영상을 비롯한 다양한 영상을 대상으로 실험한 결과 제안하는 방법이 기존의 히스토그램 평활화 기법 및 이를 개선한 방법에 비해 GSD (global standard deviation)으로 측정한 객관적 수치 측면에서 우수한 성능을 나타내고, 주관적 화질 측면에서 자연스럽고 영상의 어두운 영역 및 밝은 영역에서의 디테일 보존 성능이 우수함을 확인할 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.538-539
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• 2015

일반 영상의 화질을 개선하기 위해 다양한 알고리즘이 존재한다. 하지만 X-ray 영상의 경우 일반 영상과 특성이 다르기 때문에 기존의 화질 개선 알고리즘으로는 진단에 적합한 화질을 얻을 수 없다. 디지털 X-ray 기기로부터 처음 획득된 X-ray 영상은 데이터 범위가 일반 영상에 비해 넓고 밝기 레벨이 고르지 못하다. 특히 Chest X-ray 영상의 경우 다양한 이유로 촬영하기 때문에 갈비뼈와 혈관, 척추 뼈 등 특성이 다른 모든 부위들을 자연스럽게 개선할 필요가 있다. 본 논문은 영상의 불필요한 배경 성분을 제거하여 특정 밝기에 밀집되어 있는 데이터들의 히스토그램 범위를 확장시키고 주파수 대역 별 가중치를 조절하여 대비 및 선명도를 향상시킨다. 마지막으로 전역적 대비 개선 기법과 지역적 대비 개선 기법의 장점을 취하여 진단에 적합하도록 개선된 Chest X-ray 영상을 얻는다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.19-38
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• 2005

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.522-527
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• 2010

In this paper, a new MBHF(Morphology-Based Homomorphic filter) is presented to enhance contrast in mammographic images. The MBH filtering is performed based on the morphological sub-bands, in which an image is morphologically decomposed. The filter is designed to have optimal gain and structuring element in each sub-band through differential evolution. Experimental results show that the proposed method improves the contrast in mammographic images such that an evaluation criterion, WPSNR(Weighted Peak Signal to Noise Ratio) which takes into account human visual system is increased compared with a wavelet-based Homomorphic filter.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.85-88
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• 2016

대비 강화는 컴퓨터 비젼, 영상 처리, 패턴인식에서 전처리 과정으로 이용되며 그 역할이 중요하다. 2차원 히스토그램을 이용한 대비 강화 방법은 인접 픽셀 간의 정보를 이용해 대비를 강화시키기 때문에 1차원 히스토그램을 이용한 대비 강화 방법보다 우수하다. 2차원 히스토그램 기반 알고리즘에서 2차원 히스토그램의 인접픽셀 간의 화소값 차이에 따라 가중치를 주는 커널 (kernel)이 사용된다. 이러한 커널은 영상 마다 같은 가중치를 곱해주기 때문에 원하는 대비를 시켜주지 못하는 단점이 있다. 이에 본 논문은 2차원 히스토그램을 1차원 히스토그램으로 정사영을 시켜 평균값과 표준편차를 통해 2차원 히스토그램을 통계학적으로 분석한다. 그리고 선형회귀법을 이용하여 2차원 히스토그램의 통계적 정보에 따른 적응적 가중치 커널을 제안하고, 이를 이용하여 효율적 대비 강화를 한다. 실험 결과를 통해 제안하는 방법이 기존의 알고리즘에 비해 대비 향상 성능이 더 우수한 방법임을 확인하였다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.37-45
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• 2010

This paper proposes a novel contrast enhancement method which determines the stretching ranges based on the distribution densities of segmented sub-histogram. In order to enhance the quality of image effectively, the contrast histogram is segmented into sub-histograms based on the density in each brightness region. Then the stretching range of each sub-histogram is determined by analysing its distribution density. The higher density region is extended wider than lower density region in the histogram. This method solves the over stretching problem, because it stretches using density rate of each area on the histogram. To evaluate the performance of the proposed algorithm, the experiments have been carried out on complex contrast images, and its superiority has been confirmed by comparing with the conventional methods.