A fast marine sewage detection method for remote-sensing image

This paper presents an effective method for marine sewage detection from a remote-sensing image. It is inspired by the Grab-Cut mechanism that iterative estimation and incomplete labeling allow a considerably reduced degree of user interaction for a given quality of result. By establishing the relationship between the color feature and the object seeds, we first model object and background with Gaussian mixture model, respectively, followed by iteratively updating the parameter of model to decline the energy function. To improve the computation efficiency, we propose to extend the region of interest as background. The proposed method accounts for not only the effect of color feature, but also the geographical information. The experimental results demonstrate that the proposed method is more reliable in marine sewage detection compared to other state-of-the-art methods.