Abstract:Segmenting natural and outdoor images are challenging for most of the latest variational segmentation models. For this purpose we employ derived image data (DID) and propose a robust variational model. The DID rely on three images by utilizing image local and global statistics as well as filter image which is obtained through our design high pass filtering techniques. Then these derived image data are incorporated into our proposed energy functional which can robustly segment images having inhomogeneity, mix b… Show more
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