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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/129116

Title:	Underwater Image Restoration based on Image Blurriness and Light Absorption
Authors:	彭彥璁 Peng , Yan-Tsung Cosman, Pamela Peng , Yan-Tsung
Contributors:	資科系
Keywords:	Underwater image;image restoration;image enhancement;depth estimation;blurriness;light absorption
Date:	2017-02
Issue Date:	2020-03-05 14:40:15 (UTC+8)
Abstract:	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.
Relation:	IEEE Transactions on Image Processing, Vol.26, No.4, pp.1579 - 1594
Data Type:	article
DOI 連結:	https://doi.org/10.1109/TIP.2017.2663846
DOI:	10.1109/TIP.2017.2663846
Appears in Collections:	[資訊科學系] 期刊論文

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