Proceedings of the 2019 International Conference on Mathematics, Big Data Analysis and Simulation and Modelling (MBDASM 2019) 2019
DOI: 10.2991/mbdasm-19.2019.4
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An Improved Algorithm of Parameter Kernel Cutting Based on Complex Fusion Image

Abstract: Aiming at the problem that the color image with more detailed textures is not highly segmented in the image segmentation process, a PKGC image segmentation method based on improved edge detection difference ratio is proposed. The method first constructs an energy function by using a parametric kernel graph cutting algorithm. Then, the value of the three-channel RGB edge detection ratio of the color image is used to change the constant balance factor in the energy function to change the ratio of the data item a… Show more

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Cited by 2 publications
(2 citation statements)
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“…In order to verify the effectiveness of the algorithm, this paper selects the multi-focus image fusion (NPF) algorithm based on NSCT and pulse coupled neural network (PCNN) [25], the surface wavelet transform (SCT) [26], and the multi-focus image fusion (FGF) algorithm based on fast finite shear wave transform and guided filtering [27] for comparison. Average gradient (AG), spatial frequency (SF), mutual information MI, and edge-preserving information transfer factor QAB/F (high weight evaluation standard) were used for objective evaluation [28,29].…”
Section: Resultsmentioning
confidence: 99%
“…In order to verify the effectiveness of the algorithm, this paper selects the multi-focus image fusion (NPF) algorithm based on NSCT and pulse coupled neural network (PCNN) [25], the surface wavelet transform (SCT) [26], and the multi-focus image fusion (FGF) algorithm based on fast finite shear wave transform and guided filtering [27] for comparison. Average gradient (AG), spatial frequency (SF), mutual information MI, and edge-preserving information transfer factor QAB/F (high weight evaluation standard) were used for objective evaluation [28,29].…”
Section: Resultsmentioning
confidence: 99%
“…In order to verify the effectiveness of the algorithm, this paper selects the multi focus image fusion (NPF) algorithm based on NSCT and pulse coupled neural network (PCNN) [25], the surface wavelet transform (SCT) [26] and the multi focus image fusion (FGF) algorithm based on fast finite shear wave transform and guided filtering [27] for comparison. Average gradient (AG), spatial frequency (SF), mutual information MI and edge preserving information transfer factor QAB/F (high weight evaluation standard) were used for objective evaluation [29][30].…”
Section: Resultsmentioning
confidence: 99%