Li et al. employed a dehazing with minimum information loss and histogram distribution prior algorithm for underwater image restoration.
Drews et al. proposed an underwater dark channel prior (UDCP) algorithm based on the original dark channel prior (DCP), it introduces the defogging idea of natural image into the defogging of underwater image. Galdran et al. presented a red channel algorithm for underwater image restoration, which can compensate for the attenuation of the red channel. Underwater image restoration algorithms.In the earlier stage, polarization-based techniques were utilized to restore underwater images, but they required specialized hardware to obtain the information of different degrees of polarization. Enhancement algorithms are simple and effective because they do not consider the underwater optical imaging model. Based on the existing image enhancement techniques, underwater image enhancement algorithms selectively highlight the region of interest (ROI) or suppress the non-ROI by adjusting the pixels of the original image to improve the visibility of underwater images. Underwater image restoration algorithms aim to restore the degraded underwater image to a clearer underwater image by finding an inverse degradation of the physical degradation mechanism. Underwater image clarity techniques can be categorized into underwater image restoration and enhancement algorithms . In short, underwater images mainly suffer from color distortion, low contrast, and poor visibility. On the other hand, light of different wavelengths with different attenuation rates during the propagation of underwater media, which will lead to blurring and color distortion of underwater images . On the one hand, forward and backward scattering will result in blurring, low contrast, and poor visibility of underwater images . Fig. 1 gives an illustration of underwater optical imaging. In the underwater medium, light is affected by both absorption of water and scattering of suspended particles underwater. To fully understand the underwater scenes and make rational use of various underwater resources, it is urge to develop underwater image enhancement techniques, which can benefit the following studies, i.e., underwater target detection , underwater environmental protection , and marine biology research . However, obtaining high-quality underwater images is relatively difficult comparing with the images captured on land. The most convenient way for us to understand the underwater world is to leverage cameras. Unlike standing on the lands, people are not able to live and work in underwater even equipped with oxygen bottle. In recent years, with the continuous growth of the population and the shortage of land resources, people now pay more and more attention to the marine environment in order to exploit the underwater resources. People have always shown their strong curiosity in exploring the underwater world.
The ocean covers around 71 % of the surface in our planet.
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