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LI XU - Homepage Li Xu's home pageDeep Learning for Complex Image Processing: "Deep Edge-Aware Filters" ICML'15
Shadow Removal from a Single Image Li Xu Feihu Qi Renjie Jiang Department of Computer Science and Engineering, Shanghai JiaoTong University, P R China E-mail {nathan xu, fhqi, blizard1982}@sjtu edu cn
Unnatural L0 Sparse Representation for Natural Image Deblurring Xu and Jia [25] proposed a texture-removal strategy, ex-plained and extended in [28], to guide edge selection and detect large-scale structures The resulting edge map in each step is also a small-edge-subduedversion from the nat-ural input
Real-time Contrast Preserving Decolorization | = p(Lx − Ly)2 + (ax − ay)2 + (bx − by)2, which represents the color dissimilarity in the human vision sys-tem [Wyszecki and Stiles 2000] Eq (1) can be interpreted in view of probabilistic inference It implies that the differences of the grayscale values for two pixels x and y follow a Gaussian distribu-tion with mean δx,y
Image smoothing via lt;i gt;L lt; i gt; lt;sub gt;0 lt; sub gt; gradient minimization We regard our method as complementary to prior smoothing approaches Finally, interactive image editing needs to select regions of interest with accurate boundaries Graph-cut based meth-ods [Rother et al 2004; Li et al 2004; Liu et al 2009] and segmentation [Maji et al 2011; Arbelaez et al 2011] were em-ployed