Multi-View Super Resolution for Underwater Images Utilizing Atmospheric Light Scattering Model.

The underwater environment is complex and the underwater light propagation undergoes absorption, scattering and reflection. This leads to the fact that the underwater light imaging cannot be generalized from land-based. How to use these imaging features to work better with super-resolution tasks for underwater imagery applications is still rarely studied. In this paper, we introduce the medium transmission (MT) maps to advance super-resolution tasks for underwater images. A multi-view network is designed to fuse information from the original underwater images and the MT maps, which provides information on the underlying physical properties of the water, such as the attenuation coefficients in different parts of water. By integrating information from multiple views, the proposed network can capture more of the underlying structure and features of the scene, leading to higher-quality super-resolved images. Besides, a new loss function, namely MT Loss, is developed according to the lack of details in special region of the underwater images. This loss function emphasizes the regions with less influence from the underwater environment during the underwater imaging process and therefore the network outputs a more detailed image. Finally, we compare our algorithm with state-of-the-art methods, and extensive results show that our network achieves better qualitative and quantitative performance.