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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Acknowledgements
The authors would like to thank the editor and the anonymous reviewers for their critical and constructive comments and suggestions. This work has been supported by the National Natural Science Foundation of China (Grant No. 61702262), Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (Grant No. 61861136011), Natural Science Foundation of Jiangsu Province, China (Grant No. BK20181299), Science and Technology on Parallel and Distributed Processing Laboratory (PDL) Open Fund (WDZC20195500106), Young Elite Scientists Sponsorship Program by CAST (2018QNRC001), the Fundamental Research Funds for the Central University (Grant No. 30920032201), National Science Fund of China (Grand No. U1713208), Program for Changing Scholars.
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Yao, Z., Liu, Y., Zhang, S. et al. Effective quaternion radial harmonic Fourier moments for color image representation. SIViP 15, 93–101 (2021). https://doi.org/10.1007/s11760-020-01726-z
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DOI: https://doi.org/10.1007/s11760-020-01726-z