https://scholars.lib.ntu.edu.tw/handle/123456789/607313
標題: | Image Dehazing in Disproportionate Haze Distributions | 作者: | Huang S.-C Jaw D.-W Li W Lu Z Kuo S.-Y Fung B.C.M Chen B.-H SY-YEN KUO |
關鍵字: | dark channel prior;disproportionate haze distribution;Haze removal;Demulsification;Restoration;Visibility;Background region;Dark channel priors;Foreground regions;Hybrid transmissions;Quantitative evaluation;Real world environments;State-of-the-art methods;Vision based system;Image reconstruction | 公開日期: | 2021 | 卷: | 9 | 起(迄)頁: | 44599-44609 | 來源出版物: | IEEE Access | 摘要: | Haze removal techniques employed to increase the visibility level of an image play an important role in many vision-based systems. Several traditional dark channel prior-based methods have been proposed to remove haze formation and thereby enhance the robustness of these systems. However, when the captured images contain disproportionate haze distributions, these methods usually fail to attain effective restoration in the restored image. Specifically, disproportionate haze distribution in an image means that the background region possesses heavy haze density and the foreground region possesses little haze density. This phenomenon usually occurs in a hazy image with a deep depth of field. In response, a novel hybrid transmission map-based haze removal method that specifically targets this situation is proposed in this work to achieve clear visibility restoration and effective information maintenance. Experimental results via both qualitative and quantitative evaluations demonstrate that the proposed method is capable of performing with higher efficacy when compared with other state-of-the-art methods, in respect to both background regions and foreground regions of restored test images captured in real-world environments. ? 2013 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103407383&doi=10.1109%2fACCESS.2021.3065968&partnerID=40&md5=5966c63a14fd0204a33defb06319858a https://scholars.lib.ntu.edu.tw/handle/123456789/607313 |
ISSN: | 21693536 | DOI: | 10.1109/ACCESS.2021.3065968 |
顯示於: | 電機工程學系 |
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