underwater imaging

A coarse-to-fine SR CNN (CFSRCNN) consisting of a stack of feature extraction blocks (FEBs), an enhancement block (EB), a construction block (CB) and, a feature refinement block (FRB) is proposed to learn a robust SR model.

To handle the various types of tasks in the upcoming cellular services, we can design the system with both cloud and edge computing capabilities, where the computational tasks can be partially offloaded to the ENs and the CP.

Underwater image enhancement has drawn considerable attention in both image processing and underwater vision. Due to the complicated underwater environment and lighting conditions, enhancing underwater image is a challenging problem.