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政大機構典藏 > 資訊學院 > 資訊科學系 > 期刊論文 > Item 140.119/129116

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题名:	Underwater Image Restoration based on Image Blurriness and Light Absorption
作者:	彭彥璁 Peng , Yan-Tsung Cosman, Pamela Peng , Yan-Tsung
贡献者:	資科系
关键词:	Underwater image;image restoration;image enhancement;depth estimation;blurriness;light absorption
日期:	2017-02
上传时间:	2020-03-05 14:40:15 (UTC+8)
摘要:	Underwater images often suffer from color distortion and low contrast, because light is scattered and absorbed when traveling through water. Such images with different color tones can be shot in various lighting conditions, making restoration and enhancement difficult. We propose a depth estimation method for underwater scenes based on image blurriness and light absorption, which can be used in the image formation model (IFM) to restore and enhance underwater images. Previous IFM-based image restoration methods estimate scene depth based on the dark channel prior or the maximum intensity prior. These are frequently invalidated by the lighting conditions in underwater images, leading to poor restoration results. The proposed method estimates underwater scene depth more accurately. Experimental results on restoring real and synthesized underwater images demonstrate that the proposed method outperforms other IFM-based underwater image restoration methods.
關聯:	IEEE Transactions on Image Processing, Vol.26, No.4, pp.1579 - 1594
数据类型:	article
DOI 連結:	https://doi.org/10.1109/TIP.2017.2663846
DOI:	10.1109/TIP.2017.2663846
显示于类别:	[資訊科學系] 期刊論文

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