LAUSR

Underwater images are often deteriorated with blurring, darkness, poor visual quality of low contrast, and color diminishing. This is mainly due to the fact that the light is exponentially attenuated while traveling through water and the strength of attenuation is color dependent. After constructing a simplified image formation model, this paper proposes a new strategy for single underwater image restoration. In light of different perspectives, two distinct transmission coefficient estimation approaches have been developed. One is based on the optical characteristics while the other relies on the essence of image processing knowledge. Subsequently, these two transmission maps are fused to produce the final outcome, which is adaptively weighted by their respective saliency maps. The obtained signal radiance is dissolved through point spread function deconvolution and color compensation to produce the final scene radiance. A variety of underwater images with various scenarios were exploited to evaluate the restoration performance. Experimental results demonstrated the superiority of the proposed algorithm over other competitive methods for underwater image restoration.