"Underwater photos tend to be degraded and lacking in clear details because of the 'veiling' effect of ambient light," explains Schechner. "From above the water's surface, ambient light scatters into the line of sight -- an effect commonly known as 'backscatter.' This causes poor visibility in even the clearest water." He adds that the veiling effect increases with distance, making many details undetectable.
Schechner and graduate student Nir Karpel realized that photographic images could be greatly improved by eliminating the backscatter effect. The two then developed an algorithm that -- combined with a polarizing filter readily available for $20 to $100 -- compensates for backscatter.
Once the photographs are taken using the filter, they are transferred to a computer program, which then applies the algorithm, compensating for the underwater image degradation caused by backscatter. Unlike standard photo imaging programs that treat a photographic image as a whole, the new method corrects different elements -- such as objects that are closer or distant -- individually, according to need.
According to the researchers, this process also provides estimates of underwater distances, resulting in improved picture quality and photographs with three-dimensional depth.
Schechner says the program could be placed on a chip embedded within the camera or be integrated with existing video systems to vastly improve underwater video quality. In the future, it could be utilized for a myriad of applications including engineering, marine biology and archeology, underwater mapping, recreational photography and underwater rescue. The researchers are negotiating commercialization of the program.