Single Image Dehazing via Deep Learning-based Image Restoration

Chia Hung Yeh, Chih Hsiang Huang, Li Wei Kang, Min Hui Lin

研究成果: 書貢獻/報告類型會議論文篇章

8 引文 斯高帕斯(Scopus)

摘要

Images/videos captured from outdoor visual devices are usually degraded by turbid media, such as haze, smoke, fog, rain, and snow. Haze is the most common one in outdoor scenes due to the atmosphere conditions. This paper presents a deep learning-based architecture for single image dehazing via image restoration. instead of learning an end-to-end mapping between each pair of hazy image and its corresponding haze-free one adopted by most existing approaches, we propose to transform the problem into the restoration of the image base component. By first decomposing the hazy image into the base and the detail components, haze removal can be achieved by learning a CNN (convolutional neural network) only for mapping between hazy and haze-free base components, while the detail component can be further enhanced. As a result, the final dehazed image is obtained by integrating the haze-removed base and the enhanced detail image components. Experimental results have demonstrated good efficacy of the proposed method, compared with state-of-the-art results.

原文英語
主出版物標題2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1609-1615
頁數7
ISBN(電子)9789881476852
DOIs
出版狀態已發佈 - 2019 三月 4
事件10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Honolulu, 美国
持續時間: 2018 十一月 122018 十一月 15

出版系列

名字2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings

會議

會議10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018
國家/地區美国
城市Honolulu
期間2018/11/122018/11/15

ASJC Scopus subject areas

  • 資訊系統

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