Abstract
Underwater images suffer from various degradation factors, such as blur, haze, color degradation, and marine snow. Marine snow is a type of noise, caused mostly by biological particles that fall into the ocean bottom, and which impedes proper object detection in underwater vision. A method for real-time marine snow removal from underwater color and monochrome video is presented. It is based on the proposed marine snow model, spatiotemporal patch analysis, and three-dimensional median filtering. The method was evaluated on a number of real underwater sequences endowed with the hand-annotated ground-truth data which were made available from the Internet. As shown by the experiments, the method attains high accuracy and performs in real time.
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