• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.67-72
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• 2012

In this paper, we present an image enhancement method for atmospherically degraded images using atmospheric light and transmission based on color analysis. We first generate a normalized image using maximum value of each RGB color channel. Then, each atmospheric light is estimated from RGB color channel respectively by calculating reflectance of an image. We also, generate a transmission using gamma coefficients from the Y channel of the image. We can significantly enhance the visibility of an image by using the estimated atmospheric light and the transmission. The proposed algorithm can remove atmospheric degradation components better than existing techniques because the color prevents color distortion which is common problem of existing techniques. Experimental results demonstrate that the proposed algorithm can improve visibility be removing fog, smoke, and dust.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.192-194
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• 2003

Since the details in quasi-homogeneous region will be destroyed from the conventional global image enhancement method such as histogram equalization. This defect is caused by the saturation of gray level in equalization process. So the local histogram equalization for each quasi-homogeneous region will be used in order to improve the details in the region itself. To obtain the quasi- homogeneous regions, the original image must be segmented. Here we applied the watershed transform to the interesting image. Since the watershed transform is based on mathematical morphology, therefore, the regions touch can be effectively separated. Hence two adjacent regions which have the similar gray pixels will be split off. The process will be independently applied to three different spectral images. Then three different colors are assigned to each processed image in order to produce a color composite image. By the proposed algorithm, the result image shows the better perception on image details. Therefore, the high efficiency of image classification can be obtained by using this color image.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.5
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• pp.645-652
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• 2015

In underwater, such as fish farm and sea, turbidity is increased by water droplets and various suspended, therefore light attenuation occurs depending on the depth also caused by the scattering effect of light float. In this paper, in order to improve the visibility of underwater images obtained from these aquatic environment, we propose a visibility enhancement method using a haze removal method based on dark channel prior and a trained color transform model. In order to train a color transform model, we used underwater pattern images captured from Pohang and Yeosu, and to measure the performance of the proposed method, we carried out experiment of visibility enhancement using underwater images collected from Yeosu, Geomundo and Philippines. The results show that the proposed method can improve the visibility of underwater images of various locations.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.794-797
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• 2007

We have developed the adaptive contrast ratio enhancement algorithm for mobile LCD. This algorithm aims at effective contrast ratio enhancement with minimizing degeneration of color and white balance. It also is very simple to fit mobile LCD system.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.385-388
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• 2003

In this paper, we propose a new saturation enhancement algorithm which is processed on the new color space, called Normalized YCbCr(NYCbCr). The algorithm consists of two processing unit. One is color space conversion from YCbCr to NYCbCr, and the other is using adaptive saturation mapping function(ASMF). NYCbCr color space is designed to prevent shortcomings such as luminance and hue shift of YCbCr color space and by saturation enhancement. ASMF is effective to enhance saturation properly for each image and to protect low saturation regions of color images from over-saturation. we verified our method using several color images. Experimental results show that the proposed method enhance the saturation with minimizing Luminance and Hue shift.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.368-379
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• 2010

As high-definition video is broadly used in various system such as broadcast system and digital camcorder the proper method in order to improve the quality of high-definition video is needed. In this paper, we propose an efficient method to improve color and contrast of high-definition video. In order to apply the image enhancement method to high-definition video, scale-down video of high-definition video is used and the parameter for image enhancement method is computed from small size video. To enhance the color of high-definition video, we apply color constancy method. First, we separate the video into several scenes by cut detection method. Then, we apply color constancy to each scene with same parameter. To improve the contrast of high-definition video, we use union of original image and histogram equalized image, and weight is calculated based on sorting of histogram bins. Finally, the performance of proposed method is demonstrated in experiment section.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.544-564
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• 2022

Underwater images often suffer from color distortion, blurring and low contrast, which is caused by the propagation of light in the underwater environment being affected by the two processes: absorption and scattering. To cope with the poor quality of underwater images, this paper proposes a multiscale fusion underwater image enhancement method based on channel attention mechanism and local binary pattern (LBP). The network consists of three modules: feature aggregation, image reconstruction and LBP enhancement. The feature aggregation module aggregates feature information at different scales of the image, and the image reconstruction module restores the output features to high-quality underwater images. The network also introduces channel attention mechanism to make the network pay more attention to the channels containing important information. The detail information is protected by real-time superposition with feature information. Experimental results demonstrate that the method in this paper produces results with correct colors and complete details, and outperforms existing methods in quantitative metrics.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.684-694
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• 2012

In the underwater environment, light is absorbed and scattered by water and floating particles, which makes the underwater images suffer from color degradation and limited visibility. Physically, the amount of the scattered light transmitted to the image is proportional to the distance between the camera and the object. In this paper, the proposed visibility enhancement. method utilizes depth images to estimate the light transmission and the degradation factor by the scattered light. To recover the scatter-free images without unnatural artifacts, the proposed method normalizes the degradation factor based on the value of each pixel of the image. Finally, the scatter-free images are obtained by removing the scattered components on the image according to the estimated transmission. The proposed method also considers the color discrepancies of underwater stereo images so that the stereo images have the same color appearance after the visibility enhancement. The experimental results show that the proposed method improves the color contrast more than 5% to 14% depending on the experimental images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.65-73
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• 2011

In this paper, we present a novel digital multifocusing approach using adaptive region-based histogram equalization for the multiple color-filter aperture (MCA) system with insufficient amount of incoming light. From the image acquired by the MCA system, we can estimate the depth information of objects at different distances by measuring the amount of misalignment among the RGB color planes. The estimated depth information is used to obtain multifocused images together with the process of the region-of-interests (ROIs) classification, registration, and fusion. However, the MCA system results in the low-exposure problem because of the limited size of the apertures. For overcoming this problem, we propose adaptive region-based histogram equalization. Based on the experimental results, the proposed algorithm is proved to be able to obtain in-focused images under the low light level environment.