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Difference Curvature Driven Anisotropic Diffusion for Image Denoising Using Laplacian Kernel
2013
Applied Mechanics and Materials
Image noise removal forms a significant preliminary step in many machine vision tasks, such as object detection and pattern recognition. The original anisotropic diffusion denoising methods based on partial differential equation often suffer the staircase effect and the loss of edge details when the image contains a high level of noise. Because its controlling function is based on gradient, which is sensitive to noise. To alleviate this drawback, a novel anisotropic diffusion algorithm is
doi:10.4028/www.scientific.net/amm.347-350.2412
fatcat:qj6qxh7nbfejrlpui2gqgmbv24