![]() ![]() Using a sunlight-like light source instead will make the underwater images look natural.Ĭolor correction is also known as white balance in image processing. Without considering the color cast formed in the second process, it looks like that an underwater image is captured with the scene illuminated by an unknown light source. The color cast formed in the first process is dominant, especially for the images captured in deep water. Since the object of interest called foreground is usually closer to the camera than the background, the color cast of the foreground formed in the second process is generally little. One is the light travels downward before reaching the scene and the other is the light travels to the camera after reflected by the scene. To be exact, during the light propagation in the water medium, color cast is formed in two processes. Color cast is generated due to the variation of light attenuation, which is caused by absorption and scattering, in different wavelengths. This paper focuses on the color correction of underwater images with the assumption that sunlight is the only light source. The color correction methods are used casually and there is no specialized comprehensive comparison between different color correction methods on underwater images. Most of the underwater image restoration and enhancement methods try to correct the color cast and enhance the contrast simultaneously. However, the deep-learning-based methods are hindered by the lack of large training datasets. Recently, many deep-learning-based methods have been developed for underwater image restoration and enhancement. The enhancement methods use qualitative subjective criteria to produce more visually pleasing images. ![]() The restoration methods try to reverse the underwater imaging process according to some priors, such as dark channel prior (DCP) and scene depth map. Many image formation model based (IFM-based) image restoration methods and IFM-free image enhancement methods have been raised to achieve this goal. The color cast and the contrast loss are the main consequences of underwater imaging degradation processes, and the goal of underwater image processing is to rectify the color cast and enhance visibility. However, captured underwater images are generally degraded by scattering and absorption. Underwater imaging is increasingly used in many important applications such as marine biology and archaeology, underwater surveying and mapping. The proposed method is simple yet effective and robust, which is helpful in obtaining the in-air images of underwater scenes. Qualitative and quantitative evaluations both show that the proposed method outperforms the other test methods in terms of color restoration, especially for the images with severe color cast. Third, the chromatic adaptation transform is implemented in the device-independent XYZ color space. Second, the illumination is estimated in a uniform chromatic space based on the white-patch hypothesis. First, the underwater RGB image is first linearized to make its pixel values proportional to the light intensities arrived at the pixels. With the assumption that the illumination of the scene is uniform, a chromatic adaptation-based color correction technology is proposed in this paper to remove the color cast using a single underwater image without any other information. Recovering correct or at least realistic colors of underwater scenes is a challenging issue for image processing due to the unknown imaging conditions including the optical water type, scene location, illumination, and camera settings. ![]()
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