Existing fractional-order Perona-Malik Diffusion (FOPMD) algorithms are defined as fully spatial fractional-order derivatives\n(FSFODs). However, we argue that FSFOD is not the best way for diffusion since different parts of spatial derivative play different\nroles in Perona-Malik diffusion (PMD) and derivative orders should be decided according to their roles. Therefore, we adopt a\nnovel fractional-order diffusion scheme, named external fractional-order gradient vector Perona-Malik diffusion (EFOGV-PMD),\nby only replacing integer-order derivatives of ââ?¬Å?externalââ?¬Â gradient vector to their fractional-order counterpartswhile keeping integerorder\nderivatives of gradient vector for diffusion coefficients since the ability of edge indicator for 1-order derivative is demonstrated\nboth in theory and applications. Here ââ?¬Å?externalââ?¬Â indicates the spatial derivatives except for the derivatives used in diffusion\ncoefficients. In order to demonstrate the power of the proposed scheme, some real sinograms of low-dosed computed tomography\n(LDCT) are used to compare the different performances. These schemes include PMD, regularized PMD (RPMD), and FOPMD.\nExperimental results show that the new scheme has good ability in edge preserving, is convergent quickly, has good stability for\niteration number, and can avoid artifacts, dark resulting images, and speckle effect.
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