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In this paper, we analyze and compare the performance, both in spatial and frequency domains, of different moments. Our analysis shows that Legendre and Gaussian-Hermite moments better separate image features based on different spatial modes and Gaussian-Hermite moments are less sensitive to noise. Analysis on spectral performance shows that Legendre and Gaussian-Hermite moments separate different frequency bands more effectively than others. It is also shown that Gaussian-Hermite moments give an approach to construct orthogonal features from wavelet analysis results. Experimental results are reported.
Jun Shen andWei Shen
"Analysis of moment performance", Proc. SPIE 3545, International Symposium on Multispectral Image Processing (ISMIP'98), (25 September 1998); https://doi.org/10.1117/12.323623
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Jun Shen, Wei Shen, "Analysis of moment performance," Proc. SPIE 3545, International Symposium on Multispectral Image Processing (ISMIP'98), (25 September 1998); https://doi.org/10.1117/12.323623