Object structure
Creator:

Wu, Haiyong ; Yan, Senlin

Contributor:

Makowski, Ryszard - ed. ; Zarzycki, Jan - ed.

Title:

Bivariate Hahn moments for image reconstruction

Subtitle:

.

Group publication title:

AMCS, Volume 24 (2014)

Subject and Keywords:

bivariate Hahn moments ; bivariate Hahn polynomials ; image reconstruction ; pattern recognition

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.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2014

Resource Type:

artykuł

DOI:

10.2478/amcs-2014-0032

Pages:

417-428

Source:

AMCS, volume 24, number 2 (2014) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego

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