Article
Environmental Sciences
Hong Guo, Xiaochun Wang, Hongjun Li
Summary: This paper proposes a method and index for estimating fog density using images or videos, which has the advantages of convenient operation and low costs. The effectiveness of the index is demonstrated through experiments, showing accurate estimation of fog density in images and evaluation of video defogging algorithms.
Article
Computer Science, Artificial Intelligence
Fayaz Ali Dharejo, Yuanchun Zhou, Farah Deeba, Munsif Ali Jatoi, Yi Du, Xuezhi Wang
Summary: This research introduces a new image enhancement approach for image dehazing based on dark channel prior and piecewise linear transformation, as well as contrast limited adaptive histogram equalisation. Experimental results demonstrate that the proposed method significantly improves the visibility of dark remote-sensing images and hazy natural images.
IET IMAGE PROCESSING
(2021)
Article
Meteorology & Atmospheric Sciences
H. Wang, X. Y. Zhang, P. Wang, Y. Peng, W. J. Zhang, Z. D. Liu, C. Han, S. T. Li, Y. Q. Wang, H. Z. Che, L. P. Huang, H. L. Liu, L. Zhang, C. H. Zhou, Z. S. Ma, F. F. Chen, X. Ma, X. J. Wu, B. H. Zhang, X. S. Shen
Summary: The study integrates meteorology and chemistry models to improve haze/fog prediction, and finds that relative humidity has important impacts on visibility and PM2.5, and aerosol-radiation-cloud interaction has positive effects on visibility and PM2.5 prediction.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Article
Meteorology & Atmospheric Sciences
Rui Lyu, Yanyu Wang, Yarong Peng, Wei Gao, Hequn Yang, Xinyao Tan, Qianshan He, Tiantao Cheng, Renjian Zhang
Summary: This study investigated the long-term trend of low-visibility events in China, particularly focusing on the transition from haze days to fog days around 2004. The analysis showed that the dominant factor influencing this transition was relative humidity variation, rather than aerosol change in the low atmosphere. The results provide insights into the factors affecting the occurrence of fog and haze in China over the past few decades.
ATMOSPHERIC RESEARCH
(2021)
Article
Meteorology & Atmospheric Sciences
Yingchuan Yang, Baozhu Ge, Xueshun Chen, Wenyi Yang, Zhongjie Wang, Huansheng Chen, Danhui Xu, Junhua Wang, Qixin Tan, Zifa Wang
Summary: This study investigates the relationship between atmospheric visibility and PM2.5 concentrations, relative humidity, and total column water vapor in Beijing. It identifies the key factors affecting visibility changes, with water vapor content playing a significant role in the evolution of visibility. The study also introduces a novel method to distinguish between haze and fog, providing insights into the forecasting and early warning of low visibility events.
ATMOSPHERIC RESEARCH
(2021)
Article
Meteorology & Atmospheric Sciences
Jaemin Kim, Seung Hee Kim, Hyun Woo Seo, Yi Victor Wang, Yun Gon Lee
Summary: To address urban issues caused by rapid urbanization, South Korea plans to establish a national pilot Smart City in Sejong and Busan. This study analyzed fog generation characteristics and meteorological elements during fog, and constructed machine learning models to estimate visibility.
ATMOSPHERIC RESEARCH
(2022)
Article
Geosciences, Multidisciplinary
Atefeh Jebah, Mohammad Zare, Mohammad Reza Ekhtesasi, Reza Jafari
Summary: Significant dust storms have been occurring in the Central part of Iran, particularly in the hyper-arid and arid zones of Yazd province, with increased frequency and intensity in recent years. A study conducted in the region utilized weather codes to monitor wind erosion and dust storm frequency, introducing new indices for evaluating air pollution in terms of different dust events. The findings suggest a significant increase in wind erosion and air pollution, highlighting the need for effective solutions to address these environmental challenges.
Article
Engineering, Electrical & Electronic
Alina Majeed Chaudhry, M. Mohsin Riaz, Abdul Ghafoor
Summary: This work proposes a simple and unique framework for visibility enhancement using image decomposition, adaptive boundary constraint, and quadtree-based dehazing, detail enhancement, and fusion. The proposed methodology is evaluated and compared with state-of-the-art techniques, demonstrating its effectiveness.
SIGNAL IMAGE AND VIDEO PROCESSING
(2023)
Article
Multidisciplinary Sciences
Ho Sang Lee
Summary: This paper proposes two steps to improve sandstorm images, including color balancing and dehazing methods. Color balancing improves the color balance of the images, while the dehazing method removes the blurry effect. Experimental results demonstrate that the proposed methods outperform state-of-the-art dehazing methods subjectively and objectively.
Article
Computer Science, Information Systems
Mamta Mittal, Munish Kumar, Amit Verma, Iqbaldeep Kaur, Bhavneet Kaur, Meenakshi Sharma, Lalit Mohan Goyal
Summary: The proposed fog elimination algorithm shows significant improvement in clarity and efficiency through reducing brightness and increasing contrast at different levels, as demonstrated by qualitative and quantitative analysis.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Yan Yang, Jinlong Zhang, Zhiwei Wang, Haowen Zhang
Summary: This study proposes a fast haze removal method based on the haze density classification prior, which can accurately distinguish between mist image and dense haze image, and effectively estimate the atmospheric light veil. The method utilizes the difference between maximum channel and minimum channel to reflect haze density, and uses the mid-channel of haze image for atmospheric light estimation. By eliminating the need for transmission map estimation, the proposed method can quickly and efficiently recover clear image.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Ping Juei Liu
Summary: A novel image enhancement framework is proposed to enhance the visibility of the image's content. The framework utilizes a new dehazing algorithm to achieve double-side enhancement in contrast and brightness. Experimental results demonstrate that the new dehazing algorithm outperforms others and is more compatible with the proposed framework. The proposed framework surpasses single dehazing algorithms or combinations in contrast and brightness enhancements.
Article
Economics
Luz C. Ortega, Luis Daniel Otero, Mitchell Solomon, Carlos E. Otero, Aldo Fabregas
Summary: Low visibility conditions have negative impacts on safety and traffic operations, leading to serious accidents. Due to the complexity and variability of weather variables, visibility forecasting is a challenging task for transportation agencies. This study explores the application of deep learning models using time series climatological data for single-step visibility forecasting. Five different deep learning models were developed, trained, and tested using data from weather stations in Florida, which is one of the states heavily affected by low visibility problems. The authors discuss the results of the models and suggest future research directions.
INTERNATIONAL JOURNAL OF FORECASTING
(2023)
Article
Engineering, Electrical & Electronic
Xinxin Zhang, Kaixin Xing, Qifang Liu, Da Chen, Yilong Yin
Summary: This paper presents an algorithm for removing reflections from a single image, using the l(0)-regularized dark channel sparsity prior and an l(0) gradient sparsity prior. The differences between the dark channel maps of the reflection-contaminated and reflection-free images are analyzed empirically and mathematically. A new data fidelity term is introduced to handle strong reflections and preserve high-frequency details. Quantitative evaluation on real-world image datasets demonstrates the high accuracy of the algorithm, while qualitative evaluation shows its competitive performance compared to state-of-the-art reflection removal methods.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2023)
Article
Multidisciplinary Sciences
Chen-Wei Liang, Chia-Chun Chang, Chun-Yun Hsiao, Chen-Jui Liang
Summary: This study proposed an artificial intelligence method for measuring atmospheric visibility in different topographical regions. The adjusted predictions showed strong agreement with the observation data for the five target areas, indicating high reliability. Due to obvious differences in topography, weather, and air quality, the optimal prediction model should be identified according to the conditions in each area.