online read us now
Paper details
Number 2 - June 2014
Volume 24 - 2014
Bivariate Hahn moments for image reconstruction
Haiyong Wu, Senlin Yan
Abstract
This paper presents a new set of bivariate discrete orthogonal moments which are based on bivariate Hahn polynomials
with non-separable basis. The polynomials are scaled to ensure numerical stability. Their computational aspects are discussed
in detail. The principle of parameter selection is established by analyzing several plots of polynomials with different
kinds of parameters. Appropriate parameters of binary images and a grayscale image are obtained through experimental
results. The performance of the proposed moments in describing images is investigated through several image reconstruction
experiments, including noisy and noise-free conditions. Comparisons with existing discrete orthogonal moments are
also presented. The experimental results show that the proposed moments outperform slightly separable Hahn moments for
higher orders.
Keywords
bivariate Hahn moments, bivariate Hahn polynomials, image reconstruction, pattern recognition