The sea background video has a wide range of applications in the fields of port maritime traffic management, combating illegal fishing vessels, and maritime rescue. However, the target pixel size in the sea background video is quite small, so increasing the resolution of the target has important practical significance. There are a lot of ripples in the sea background video, which leads to poor video super-resolution effect. We propose a video super-resolution algorithm (CARVSR) in sea background based on the channel attention mechanism. The algorithm adds spatio-temporal 3D learning convolution to the fusion module, which suppresses the interference of ripples on super-resolution reconstruction, and adds channel attention mechanism to the reconstruction module, which enhances the feature expression to reconstruction and improves super-resolution reconstruction quality. Experimental results show that the algorithm effectively improves the superresolution reconstruction effect of sea background video.
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