Abstract
Image moments based on orthogonal manner play an important role in image processing and image analysis tasks. Although many variants have been proposed, there is still big room to reduce the geometrical errors and numerical errors. To address this issue, we propose an effective quaternion radial harmonic Fourier moments (Q-RHFMs) for color image representation. We compare the Q-RHFMs with other image moments and deep data-driven features, on multiple tasks including image reconstruction, watermarking and retrieval. Experimental results show the priorities of Q-RHFMs over other moments and deep features. The codes are available at https://github.com/ZlyaoNjust/Q-RHFMs .
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