• Journal of Environmental Science International
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• v.26 no.6
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• pp.767-778
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• 2017

This research investigates the characteristics of metallic and ionic elements in $PM_{10}$ and $PM_{2.5}$ on haze day and non-haze day in Busan. $PM_{10}$ concentration on haze day and non-haze day were 85.75 and $33.52{\mu}g/m^3$, respectively, and $PM_{2.5}$ on haze day and non-haze day were 68.24 and $23.86{\mu}g/m^3$, respectively. Contribution rate of total inorganic water-soluble ion to $PM_{10}$ mass on haze day and non haze day were 58.2% and 61.5%, respectively, and contribution rate of total water-soluble ion to $PM_{2.5}$ mass on haze day and non haze day were 58.7% and 64.7%, respectively. Also, contribution rate of secondary ion to $PM_{10}$ mass on haze day and non haze day were 52.1% and 47.5%, respectively, and contribution rate of secondary ion to $PM_{2.5}$ mass on haze day and non haze day were 54.4% and 53.6%, respectively. AC (anion equivalents)/CE (cation equivalents) ratio of $PM_{10}$ mass on haze day and non haze day were 1.09 and 1.0, respectively, and AC/CE ratios of $PM_{2.5}$ mass on haze day and non haze day were 1.12 and 1.04, respectively. Also, SOR (Sulfur Oxidation Ratio) of $PM_{10}$ mass on haze day and non haze day were 0.32 and 0.17, respectively, and SOR of $PM_{2.5}$ on haze day and non haze day were 0.30 and 0.15, respectively. Lastly, NOR (Nitrogen Oxidation Ratio) of $PM_{10}$ on haze day and non haze day were 0.17 and 0.08, respectively, and NOR of $PM_{2.5}$ on haze day and non haze day were 0.13 and 0.06, respectively.

• Journal of Korea Multimedia Society
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• v.25 no.9
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• pp.1266-1272
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• 2022

With the recent development of computer vision technology, image processing-based mechanical devices are being developed to realize autonomous driving. The camera-taken images of image processing-based machines are invisible due to scattering and absorption of light in foggy conditions. This lowers the object recognition rate and causes malfunction. The safety of the technology is very important because the malfunction of autonomous driving leads to human casualties. In order to increase the stability of the technology, it is necessary to apply an efficient haze removal algorithm to the camera. In the conventional haze removal method, since the haze removal operation is performed regardless of the haze concentration of the input image, excessive haze is removed and the quality of the resulting image is deteriorated. In this paper, we propose an automatic haze removal method that removes haze according to the haze density of the input image by applying Ngo's Haziness Degree Evaluator (HDE) to Kim's haze removal algorithm using Hazy Particle Map. The proposed haze removal method removes the haze according to the haze concentration of the input image, thereby preventing the quality degradation of the input image that does not require haze removal and solving the problem of excessive haze removal. The superiority of the proposed haze removal method is verified through qualitative and quantitative evaluation.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.32-42
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• 2017

This paper proposes a new haze removal method for moving image sequence. Since the conventional dark channel prior haze removal method adjusts each color component separately in RGB color space, there can be severe color distortion in the haze removed output image. In order to resolve this problem, this paper proposes a new haze removal scheme that adjusts luminance and saturation components in HLS color space while retaining hue component. Also the conventional dark channel prior haze removal method is developed to obtain best haze removal performance for a single image. Therefore, if it is applied to a moving image sequence, the estimated parameter values change rapidly and the haze removed output image sequence shows unnatural glitter defects. To overcome this problem, a new parameter estimation method using Kalman filter is proposed for moving image sequence. Experimental results demonstrate that the haze removal performance of the proposed method is better than that of the conventional dark channel prior method.

• Design & Manufacturing
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• v.15 no.4
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• pp.32-36
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• 2021

In this study, the cause of the decrease in transmittance of the outer lens among the causes of the decrease in the amount of light in the automobile headlamp was identified, and the improvement method was selected to determine the effect. The causes of defects that lower the transmittance of the outer lens are divided into a moisture problem and a haze problem. The moisture problem is caused by the temperature difference between the inside and the outside of the head lamp, and the haze problem occurs when the heat inside the head lamp evaporates the haze component contained in the plastic material and attaches it to the outer lens. In order to improve the haze problem that occurs in plastic raw materials, the structures of the bulb light source type headlamp and the LED chip light source type headlamp were analyzed. Among them, the housing material of the LED chip light source type headlamp, which is structurally prone to haze gas, was selected as the test target. In the mass-production injection process of the housing, the drying process was selected as a method to minimize haze gas without adding a separate production process. After extracting a sample every drying time at a constant drying temperature, the sample was put into a haze tester and the residual amount of haze gas was measured. As a result, it was confirmed that the residual amount of Haze gas in the material decreased as the drying time increased.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.1
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• pp.73-86
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• 2011

Haze phenomena were analyzed to assess the impact of long range transport process on the air quality of Seoul and Busan. We statistically classified haze days observed in both Seoul and Busan into two types of haze cases: stagnant case and long-range transport case, and analyzed the air pollutant levels comparatively for each of the two cases for the period of 2000~2007. The results showed that the long-range transport haze case occurs less frequently with the occurrence frequency of 35.5% than stagnant case with the occurrence frequency of 64.5%. During the observed all haze days, all pollutants have high concentration in comparison with those under other meteorological conditions (Rain, Mist, Dust, Clear, Rain+Mist) except for only $PM_{10}$ of Dust case where its level shows highest among total 6 categorized conditions. The long range transport haze case shows similar levels of $PM_{10}$ and $NO_2$, but higher $SO_2$ and lower $O_3$ compared with stagnant haze cases, suggesting the importance of sulfur chemistry for long range transport haze case and local photochemistry for stagnant haze case. In addition, by employing the NOAA/HYSPLIT-4 backward trajectory model, we subdivided the long range transport haze cases into two different sources: urban anthropogenic high emission areas of central China, and natural emission sources over north China and/or Mongolia. The former long range transport haze case shows higher occurrence (with Seoul 70% and Busan 85%) than the latter haze case (with Seoul 30% and Busan <10%). This is also implying that the long haze phenomena occurred over Korea have been influenced by not only the anthropogenic emissions but also the natural dust emissions. These both emission sources can be good contributors in calculating the source-receptor relationship over Korean atmospheric environment.

• Journal of Environmental Science International
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• v.26 no.6
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• pp.751-765
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• 2017

This research investigates the characteristics of meteorological variation and fine particles ($PM_{10}$ and $PM_{2.5}$) for case related to the haze occurrence (Asian dust, long range transport, stationary) in Busan. Haze occurrence day was 559 days for 20 years (from 1996 to 2015), haze occurrence frequency was 82 days (14.7%) in March, followed by 67 days (12.0%) in February and 56 days (10.0%) in May. Asian dust occurred most frequently in spring and least in winter, whereas haze occurrence frequency was 31.5% in spring, 29.7% in winter, 21.1% in fall, and 17.7% in summer. $PM_{10}$ concentration was highest in the occurrence of Asian dust, followed by haze and haze + mist, whereas $PM_{2.5}$ concentration was highest in the occurrence of haze. These results indicate that understanding the relation between meteorological phenomena and fine particle concentration can provide insight into establishing a strategy to control urban air quality.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.212-218
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• 2022

The performance of vision-based intelligent systems, such as self-driving cars and unmanned aerial vehicles, is subject to weather conditions, notably the frequently encountered haze or fog. As a result, studies on haze removal have garnered increasing interest from academia and industry. This paper hereby presents a 4K-capable hardware implementation of an efficient haze removal algorithm with the following two improvements. First, the depth-dependent haze distribution is predicted using a linear model of four haze-relevant features, where the model parameters are obtained through maximum likelihood estimates. Second, the approximated quad-decomposition method is adopted to estimate the atmospheric light. Extensive experimental results then follow to verify the efficacy of the proposed algorithm against well-known benchmark methods. For real-time processing, this paper also presents a pipelined architecture comprised of customized macros, such as split multipliers, parallel dividers, and serial dividers. The implementation results demonstrated that the proposed hardware design can handle DCI 4K videos at 30.8 frames per second.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1477-1482
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• 2022

Haze is a local weather phenomenon in which very small droplets float in the atmosphere, and the amount and characteristics of haze may vary depending on the region. In particular, these haze reduce visibility, which can cause air traffic interference and vehicle traffic accidents, and degrade the quality of security CCTVs and so on. Therefore, in the past 10 years, research on haze removal has been actively conducted to reduce damage caused by haze. In this study, local haze removal is performed by weight generation using a haziness degree evaluator to adaptively respond to haze-free, homogeneous haze, and non-homogeneous haze cases. And the proposed method improves the limitations of the existing static haze removal method, which assumes that there is haze in the input image and removes the haze. We also demonstrate the superiority of the proposed method through quantitative and qualitative performance evaluations with benchmark algorithms.

• Journal of Microbiology and Biotechnology
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• v.31 no.4
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• pp.510-519
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• 2021

The pathological impact of haze upon the phyllosphere microbiota awaits investigation. A moderate degree of haze environment and a clean control were selected in Chengdu, China. Artemisia argyi, a ubiquitously distributed and extensively applied Chinese herb, was also chosen for experiment. Total genome DNA was extracted from leaf samples, and for metagenome sequencing, an Illumina HiSeq 2500 platform was applied. The results showed that the gene numbers of phyllosphere microbiota derived from haze leaves were lower than those of the clean control. The phyllosphere microbiota derived from both haze and clean groups shared the same top ten phyla; the abundances of Proteobacteria, Actinomycetes and Anorthococcuso of the haze group were substantially increased, while Ascomycetes and Basidiomycetes decreased. At the genus level, the abundances of Nocardia, Paracoccus, Marmoricola and Knoelia from haze leaves were markedly increased, while the yeasts were statistically decreased. KEGG retrieval demonstrated that the functional genes were most annotated to metabolism. An interesting find of this work is that the phyllosphere microbiota responsible for the synthesis of primary and secondary metabolites in A. argyi were significantly increased under a haze environment. Relatively enriched genes annotated by eggNOG belong to replication, recombination and repair, and genes classified into the glycoside hydrolase and glycosyltransferase enzymes were significantly increased. In summary, we found that both structure and function of phyllosphere microbiota are globally impacted by haze, while primary and secondary metabolites responsible for haze tolerance were considerably increased. These results suggest an adaptive strategy of plants for tolerating and confronting haze damage.

• Journal of Broadcast Engineering
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• v.21 no.5
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• pp.770-781
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• 2016

As a result of reducing color information and edge information, object distinction in haze image occurs with difficulty. One of the famous defogging algorithm is haze removal by using 'Dark Channel Prior(DCP)', which is used to predict for transmission rate using color information of an image and eliminates haze from the image. But, In case that haze rate is estimated under color information, there is a miscalculated issue which is posed by haze rate and transmission in area with high brightness such as a white object or a light source. In this paper, We deal with a miscalculated issue by correcting from around haze rate, after application of color normalization used by main white part of image haze. Moreover, We calculation improved transmission based on the result of improved haze rate estimation. And then haze image quality is developed through refining transmission.