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- W4320913745 abstract "Orthogonal moments based on Laguerre polynomials, especially the quaternion representation of fractional-order orthogonal moments have attracted interest in the imaging field. However, most of the existing quaternion fractional-order color orthogonal moments (QFr-COMs) based on Laguerre polynomials are constructed on Cartesian coordinate space and do not have direct rotation geometric invariance. Inspired by the idea of polynomial transformation, we present a weighted radial normalized fractional-order generalized Laguerre polynomials (WRNFr-GLPs) in polar coordinate space. On the basis, a new set of quaternion fractional-order weighted generalized Laguerre–Fourier moments (QFr-WGLFMs) is proposed and a fast and reliable computing method for geometric invariance of QFr-WGLFMs also is introduced in this paper. Theoretical analyses and experimental results showed that the proposed QFr-WGLFMs and moment invariants offer enhanced image reconstruction and pattern recognition compared with the existing quaternion fractional-order-based orthogonal moments and deep learning-based methods, especially under the conditions of image processing with noise and smooth filtering." @default.
- W4320913745 created "2023-02-16" @default.
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- W4320913745 date "2023-05-01" @default.
- W4320913745 modified "2023-10-02" @default.
- W4320913745 title "Quaternion fractional-order weighted generalized Laguerre–Fourier moments and moment invariants for color image analysis" @default.
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- W4320913745 doi "https://doi.org/10.1016/j.image.2023.116941" @default.
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