Image sharpening by morphological filtering
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摘要
This paper introduces a class of iterative morphological image operators with applications to sharpen digitized gray-scale images. It is proved that all image operators using a concave structuring function have sharpening properties. By using a Laplacian property, we introduce the underlying partial differential equation that governs this class of iterative image operators. The parameters of the operator can be determined on the basis of an estimation of the amount of blur present in the image. For discrete implementations of the operator class it is shown that operators using a parabolic structuring function have an efficient implementation and isotropic sharpening behavior.
论文关键词:Image sharpening,Mathematical morphology,Flat and quadratic structuring functions,Slope transform,Partial differential equations,Document processing
论文评审过程:Received 10 December 1998, Revised 2 May 1999, Accepted 23 June 1999, Available online 7 June 2001.
论文官网地址:https://doi.org/10.1016/S0031-3203(99)00160-0