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Image Inpainting Models Using Fractional Order Anisotropic Diffusion
2016
International Journal of Image Graphics and Signal Processing
Conventional approaches to sampling images use Shannon theorem, which requires signals to be sampled at a rate twice the maximum frequency. This criterion leads to larger storage and bandwidth requirements. Compressive Sensing (CS) is a novel sampling technique that removes the bottleneck imposed by Shannon's theorem. This theory utilizes sparsity present in the images to recover it from fewer observations than the traditional methods. It joins the sampling and compression steps and enables to
doi:10.5815/ijigsp.2015.10.01
fatcat:5e7ea7po45c3zfl4b74hhkvgpa