Abstract
The topic of underwater (UW) image colour correction and restoration has gained significant scientific interest in the last couple of decades. There are a vast number of disciplines, from marine biology to archaeology, that can and need to utilise the true information of the UW environment. Based on that, a significant number of scientists have contributed to the topic of UW image colour correction and restoration. In this paper, we try to make an unbiased and extensive review of some of the most significant contributions from the last 15 years. After considering the optical properties of water, as well as light propagation and haze that is caused by it, the focus is on the different methods that exist in the literature. The criteria for which most of them were designed, as well as the quality evaluation used to measure their effectiveness, are underlined.
Highlights
The synthesis of an underwater (UW) image is an intricate procedure that is affected by a plethora of effects that are usually ignored in images captured in air [1]
Since there is no ground truth information for comparison, the evaluation is usually done through visual inspection of the final result, or in some cases, with the use of colour charts, even though the latter is more commonly used in the cases of image restoration techniques
We tried to provide a coherent and unbiased literature review on methodologies engaged with the topic of UW image colour correction from the last 10–15 years, something that has not be done in such an extent since 2010
Summary
The synthesis of an underwater (UW) image is an intricate procedure that is affected by a plethora of effects that are usually ignored in images captured in air (e.g., uneven spatial illumination, colour dependent attenuation, backscatter, etc.) [1]. On the other hand, utilise the image formation model to restore the degraded image Such models utilise the optical properties of water, camera to object distance and camera-specific information, such as the response function. Even though methodologies such as those presented in [3,4,5,6,7,8,9,10] and thoroughly described by Schettini and Corchs, are considered outdated, they were the foundations for today’s advancements in UW image colour correction and restoration. Using the camera to object distance as well as the true RGB values of colour charts in the scene, the coefficients of the revised model are estimated”. “RGB angular error ψ between the six grayscale patches of each chart and a pure gray colour, averaged per chart
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