• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.85-88
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• 2024

안개 영상은 먼지, 안개 등의 원인으로 영상 내의 물체가 흐리게 보이며, 빛의 산란으로 인하여 영상의 밝기가 높다. 기존의 다크 채널 방식은 하늘 영역을 따로 처리하지 않고, 안개 영상에서 얻어지는 다크채널을 바탕으로 전달량을 추정한다. 이러한 방식은 안개 영상 내 하늘 영역이 왜곡되는 문제가 발생하게 된다. 이와 같은 문제점을 해결하기 위하여 본 논문에서는 영상의 반전, 유클리드, 그리고 감마보정을 이용한 적응형 전달량을 추정하여 성능을 개선하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.819-824
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• 2021

As technologies related to image processing such as autonomous driving and CCTV develop, fog removal algorithms using a single image are being studied to improve the problem of image distortion. As a method of predicting fog density, there is a method of estimating the depth of an image by generating a depth map, and various fog features may be used as training data of the depth map. In addition, it is essential to implement a hardware capable of processing high-definition images in real time in order to apply the fog removal algorithm to actual technologies. In this paper, we implement NLCV (Normalize Local Coefficient of Variation), a feature of fog based on coefficient of variation, in hardware. The proposed hardware is an FPGA implementation of Xilinx's xczu7ev-2ffvc1156 as a target device. As a result of synthesis through the Vivado program, it has a maximum operating frequency of 479.616MHz and shows that real-time processing is possible in 4K UHD environment.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 1999.10a
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• pp.67-69
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• 1999

산성물질들은 구름이나 안개가 생성될 때 내부로 녹아 들어가거나, 비가 내릴 때 녹아 들어가 구름, 안개, 비 중에 많은 양이 존재하며, 이 과정이 기체상 물질들이 대기 중에서 제거되는 주요한 과정이다. 구름이나 안개, 비 중에서 직접 산성오염물질이 생성되는 액상반응도 있고, 주로 아황산가스의 산화반응이 기여하고 있다고 알려져 있다(Hegg and Hobbs, 1978). 이렇게 생성된 대기 중 산성물질들은 대기에서 지표면으로 내려와 식물, 하천수, 호소수, 토양, 건축물 등에 영향을 준다.(중략)

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.149-151
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• 2002

산성을 유발하는 물질들은 대기 중에서 비나 눈, 안개, 구름 등에 유입되어 강하하는 습성강하와 기체상 입자상 물질의 형태로 지표로 이동하는 건성강하를 통해 대기 중에서 제거된다. 습성강하물 중 안개는 비보다 입자의 크기가 매우 작고, 수분량이 적으며, 대기 중에 체제하는 시간이 매우 길어 대기 중에서 오염물질이 계속 유입되므로 비보다 오염물질의 농도가 매우 높게 나타난다. (중략)

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.131-143
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• 2014

We propose a no-reference perceptual fog density and visibility prediction model in a single foggy scene based on natural scene statistics (NSS) and perceptual "fog aware" statistical features. Unlike previous studies, the proposed model predicts fog density without multiple foggy images, without salient objects in a scene including lane markings or traffic signs, without supplementary geographical information using an onboard camera, and without training on human-rated judgments. The proposed fog density and visibility predictor makes use of only measurable deviations from statistical regularities observed in natural foggy and fog-free images. Perceptual "fog aware" statistical features are derived from a corpus of natural foggy and fog-free images by using a spatial NSS model and observed fog characteristics including low contrast, faint color, and shifted luminance. The proposed model not only predicts perceptual fog density for the entire image but also provides local fog density for each patch size. To evaluate the performance of the proposed model against human judgments regarding fog visibility, we executed a human subjective study using a variety of 100 foggy images. Results show that the predicted fog density of the model correlates well with human judgments. The proposed model is a new fog density assessment work based on human visual perceptions. We hope that the proposed model will provide fertile ground for future research not only to enhance the visibility of foggy scenes but also to accurately evaluate the performance of defog algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.326-329
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• 2011

안개나 스모그 등으로 인한 영상의 왜곡에 대해 Dark Channel Prior 를 이용해 안개제거를 하면 깨끗한 결과 영상을 얻을 수 있다. 하지만 이 기법에서 전달량을 정련할 때 많은 시간이 걸리는데 계산 속도 면을 개선하기 위해 Gaussian Filter 를 사용해 정련한다. 이 때 단순한 Gaussian Filter 를 사용하게 되면 결과영상에서 후광효과가 생기게 된다. 후광효과를 줄이기 위해 본 논문에서 제안한 적응 Gaussian Filter 를 사용해 영상을 복원시킨다.

• Journal of the Korea Society of Computer and Information
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• v.19 no.7
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• pp.9-16
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• 2014

Since the haze removal algorithm using dark channel prior was introduced, many researches for improving processing speed have been addressed even if it presented impressive results. Remarkable one is using median dark channel prior. Although it has been considered as a very attactive method, processing speed is as low as ever. So, a parallel memory model which is suitable for SIMD architecture processing haze removal on high-definition images in high-speed is introduced in this paper. The proposed parallel memory model allows to access n pixels simultaneously. It is also support stride 3, 5, 7, and 11 in order to execute convolution mask operations, e.g., median filter. The proposed parallel memory model can therefore support enough data bandwidth to process the algorithm using median dark channel prior in high-speed.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.118-127
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• 2017

We propose the dehazing algorithm which consists of two main parts, the derivation of the Atmospheric light and adaptive transmission map. In the getting the Atmospheric light value, we utilize the quad-tree partitioning where the depth of the partitioning is decided based on the difference between the averaged pixel values of the parent and children blocks. The proposed transmission map is adaptive for each pixel by using the parameter ${\beta}(x)$ to make the histogram of the pixel values in the map uniform. The simulation results showed that the proposed algorithm outperforms the conventional methods in the respect of the visual quality of the dehazed images and the computational complexity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.376-380
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• 2015

This paper proposes new recognition method of road lanes misty day. The method enables autonomous-driving of cars and the safety of the drivers while driving with bad visibility in foggy roads. The proposed method, firstly, determines whether the foggy or not according to pixel number distributions and starting point of the fog period from input images. If it is foggy then the median filter's size of the Retinex algorithm is set to 1000 or more and it performs histogram equalization and normalization. The computer simulation results show that the proposed method can recognize better long distances and fine detection than earlier methods.

• Journal of IKEEE
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• v.26 no.3
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• pp.401-407
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• 2022

Recently, image processing technology for autonomous driving by recognizing objects and lanes through camera images to realize autonomous vehicles is being studied. Haze reduces the visibility of images captured by the camera and causes malfunctions of autonomous vehicles. To solve this, it is necessary to apply the haze removal function that can be processed in real time to the camera. Therefore, in this paper, the fog removal method of Sim with excellent performance is implemented with hardware capable of real-time processing. The proposed hardware was designed using Verilog HDL, and FPGA was implemented by setting Xilinx's xc7z045-2ffg900 as the target device. As a result of logic synthesis using Xilinx Vivado program, it has a maximum operating frequency of 276.932MHz and a maximum processing speed of 31.279fps in a 4K (4096×2160) high-resolution environment, thus satisfying the real-time processing standard.