Underwater-Image-Restoration-based-on-Image-Blurriness-and-Light-Absorption

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Underwater-Image-Restoration-based-on-Image-Blurriness-and-Light-Absorption

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# Underwater-Image-Restoration-based-on-Image-Blurriness-and-Light-Absorption, IEEE Transactions on Image Processing, 2017

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 it difficult to do restoration and enhancement. In this paper, 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. The previous IFM-based image restoration methods estimate scene depth based on the dark channel priors or the maximum intensity prior, which are frequently invalidated by the lighting conditions in underwater images, leading to poor restoration and enhancement results, while the proposed method, which estimates underwater scene depth more accurately, is more applicable for underwater image restoration. Experimental results on restoring real and synthesized underwater images demonstrate the proposed method outperforms other IFM-based underwater image restoration methods.

![Flowchart-1](https://user-images.githubusercontent.com/56446649/160263589-41dcb658-1a02-452d-81ff-86ecff2d7c71.png)

Underwater-Image-Restoration-based-on-Image-Blurriness-and-Light-Absorption

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