1 January 2007 Comparative analysis of pattern reconstruction using orthogonal moments
Author Affiliations +
Optical Engineering, 46(1), 017002 (2007). doi:10.1117/1.2432878
Abstract
We present a detailed analysis of the reconstruction of gray-level images using orthogonal moments with respect to the basis sets of Zernike, Fourier-Mellin, Chebyshev-Fourier, and pseudo-Jacobi-Fourier polynomials. As test images, we use Ronchigrams with different numbers of fringes as high-spatial-frequency components. The evaluation of image reconstruction between orthogonal moment sets is made in terms of different metrics. These measurements are the normalized image reconstruction error, the overall activity level in each image with respect to spatial frequency variations, the root-mean-square contrast, the total number of reconstructed fringes, the coordinate transformations of the input image, and the number of moment orders. Moreover, a method of denoising the input image based on the Daubechies wavelet transform is implemented to compute the signal-to-noise ratio. Numerical computations show that, for the Ronchigram reconstructions, the performance of Zernike moments is better than that of the other basis sets of orthogonal moments.
Alfonso Padilla-Vivanco, Gonzalo Urcid-Serrano, Fermín-Solomon S. Granados-Agustín, Alejandro Cornejo Rodriguez, "Comparative analysis of pattern reconstruction using orthogonal moments," Optical Engineering 46(1), 017002 (1 January 2007). http://dx.doi.org/10.1117/1.2432878
JOURNAL ARTICLE
15 PAGES


SHARE
KEYWORDS
Signal to noise ratio

Image restoration

Optical engineering

Image filtering

Image processing

Spatial frequencies

Wavelet transforms

RELATED CONTENT


Back to Top