Bivariate Hahn moments for image reconstruction
نویسندگان
چکیده
منابع مشابه
Bivariate Hahn moments for image reconstruction
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 p...
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Orthogonal moments are recognized as useful tools for object representation and image analysis. It has been shown that the recently developed discrete orthogonal moments have better performance than the conventional continuous orthogonal moments. In this paper, a new set of discrete orthogonal polynomials, namely Hahn polynomials, are introduced. The related Hahn moment functions defined on thi...
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In this paper, we introduce a set of discrete orthogonal functions known as dual Hahn polynomials. The Tchebichef and Krawtchouk polynomials are special cases of dual Hahn polynomials. The dual Hahn polynomials are scaled to ensure the numerical stability, thus creating a set of weighted orthonormal dual Hahn polynomials. They are allowed to define a new type of discrete orthogonal moments. The...
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We consider orthogonal polynomials in two variables whose derivatives with respect to x are orthogonal. We show that they satisfy a system of partial differential equations of the form α(x, y)∂ x −→ Un + β(x, y)∂x −→ Un = Λn −→ Un, where degα ≤ 2, deg β ≤ 1, −→U n = (Un0, Un−1,1, · · · , U0n) is a vector of polynomials in x and y for n ≥ 0, and Λn is an eigenvalue matrix of order (n+ 1)× (n+ 1)...
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ژورنال
عنوان ژورنال: International Journal of Applied Mathematics and Computer Science
سال: 2014
ISSN: 2083-8492
DOI: 10.2478/amcs-2014-0032