Sea-Thru: A Methodology for Removing Water From Underwater Images

Let's see what is sea-thru means: 

Sea-thru is an algorithm using the Akkaynak Treibitz underwater image formation model for color reconstruction of underwater images. 

Sea-thru Brings Clarity to Underwater Photos 

Why Sea-thru is method is introduced? 

Large chunk of underwater image datasets are generated every day that capture important information regarding the state of our oceans, but they cannot be efficiently examine with powerful computer vision and machine learning algorithms because water degrades images too severely for automated analysis.  

Existing methods that attempt to restore lost colors and contrast perform poorly and, as a result, the analysis of most underwater imagery requires costly manual effort, affecting the pace at which marine science moves forward. 

• As a result a fundamental reason for this poor performance is the common use of an atmospheric image formation model for the ocean. Here comes the introduction of the Sea-thru algorithm that successfully removes water from underwater images in a rapid, objective, and repeatable way, creating exciting opportunities for the future of underwater exploration and conservation. 

How does Sea-thru work? 

• It has scope as input (RGB-D method)  

• It does not need a color chart (more later)  

• It does not need knowledge of optical water type  

• It does not require forward-facing imaging 

First method to use the Akkaynak-Treibitz image formation model (“revised” model)  

• Derived for the ocean, physically accurate  

• Meticulously tested & validated underwater  

• Different coefficients for attenuation and backscatter  

• Attenuation coefficient is not a constant per image 

Sea-thru's image analysis factors in the physics of light absorption and scattering in the atmosphere, compared with that in the ocean, where the particles that light interacts with are much larger. Then the program effectively reverses image distortion from water pixel by pixel, restoring lost colors. 

Instead, Akkaynak’s algorithm calculates how much each pixel of the original image was distorted by the water and then shifts the image to display its true colors. 

Before Sea-Thru 

After Sea-Thru 

Conclusion: 

The results look almost waterless as if the images had been taken on land. It called as Sea-thru, as it have a huge positive impact on underwater work by coral reef biologists, ecologists, climate scientists, naturalists. 

Underwater object detection is an essential step in image processing and it plays a vital role in several applications such as the repair and maintenance of sub-aquatic structures and marine sciences. 

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