An approach of image decomposition for underwater target detection by inhomogeneous illumination based on G-Space and PDE

This paper presents a new approach of image decomposition for underwater target detection by inhomogeneous illumination based on G-Space and Partial Differential Equation (PDE). Underwater target images with high contrast visibility (less back-scattering) can be obtained within the inhomogeneous illumination field which power density is allocated inversely propotional to the rule of the light attenuation in water medium. Then the image f is decomposed into a sum of two functions u + v, where u component is modeled by a function of bounded variation (a cartoon or sketchy approximation of f), while v component representing the texture or noise is modeled by an oscillatory function. In this paper, the Vese-Osher(VO) model and Mumford-Shah-G(MS-G) model based on G-Space and PDE are introduced for texture image extraction. And the experimental results show that it's effective to obtain the cartoon and texture components as well as edge component of the underwater targets by MS-G model, which can be applied to further procedures such as image reconstruction and object recognition for underwater target detection.