1. Introduction
The integral transforms have wide applications in many branches of physics, engineering, mathematics and in other scientific disciplines. There are many applications of the integral transforms to differential, integral, and integro-differential equations, and in the theory of special functions. In particular, the integral transform technique can be applied to derive the solutions of integral equations of convolution type, integral equations, differential equations, or integro-differential equations. The literature in this subject is huge and includes many research papers and books. For more details regarding this subject, we refer the readers to [
1,
2,
3,
4,
5,
6,
7]. Integral transforms are also used in the solutions of problems regarding mathematical modelling [
8,
9].
In this article, we focus on just Fourier transform which is an integral transform. The most important use of the Fourier transformation is to solve many of the partial differential equations of the mathematical physics, such as Laplace, Heat, and Wave equations. Some applications of the Fourier transform include vibration analysis, sound engineering, communication, data analysis, etc. [
10,
11,
12,
13,
14]. The Fourier transform is also an important image processing tool, especially in transformation, representation, and encoding, smoothing and sharpening images [
5]. By comparing with the signal process that uses one-dimensional Fourier transform in imaging analysis, two- or multi-dimensional Fourier transforms are being used. Fourier transform has been widely used in the fields of image analysis.
Consider the following differential equation
where
are real parameters and
n is a positive integer. According to [
15], this equation has generally six sequences of orthogonal polynomial solutions. Three of them are Jacobi, Laguerre and Hermite infinitely orthogonal polynomials [
16] and three other ones, which are denoted by
,
and
, are finitely orthogonal with respect to the F sampling, inverse Gamma and T sampling distributions, respectively (see [
17,
18]).
The study of orthogonal polynomials and their transformations have been the subject of many papers during the last several years. The families of orthogonal polynomials which are mapped onto each other can be introduced by using the well-known Fourier transform or other integral transforms [
19]. For example, Hermite functions are eigenfunctions of a Fourier transform (see [
20,
21,
22,
23]). Likewise, the Jacobi polynomials are mapped onto the continuous Hahn polynomials [
20] and by the Fourier-Jacobi transform, Jacobi polynomials are mapped onto the Wilson polynomials [
23]. In [
24], new examples of orthogonal functions are obtained via Fourier transforms of the generalized Ultraspherical polynomials and the generalized Hermite polynomials. In [
25], the Fourier transform of Routh-Romanovski polynomials is investigated. Furthermore, via the Fourier transforms of the finite classical orthogonal polynomials
and
, and two symmetric sequences of finite orthogonal polynomials, new families of orthogonal functions are introduced in [
21,
26].
Recently, in [
27] some new families of orthogonal functions in two variables were introduced by using Fourier transforms of specific functions derived from two-variable polynomials defined in [
28,
29] and then using the Parseval identity their orthogonality relations have been obtained. Also, in [
30] the authors have defined finite bivariate orthogonal polynomials by using a Koornwinder’s method [
28].
Motivated by papers on Fourier transforms of univariate orthogonal polynomials mentioned above, a similar approach in those papers has been developed for two-dimensional Fourier transforms. This approach allows us to derive new families of bivariate orthogonal functions. Also, a similar approach can be applied for multivariate orthogonal polynomials and their properties can be investigated.
The aim of this paper is to obtain new families of bivariate orthogonal functions by two-dimensional Fourier transforms of bivariate finite orthogonal polynomials given in [
30] by means of Koorwinder’s method. The rest of the article is organized as follows: In
Section 2, we first remind three classes of finite univariate orthogonal polynomials in [
18] and then present fifteen classes of finite bivariate orthogonal polynomials which are introduced in [
30]. In
Section 3, via Fourier transforms of finite bivariate orthogonal polynomials, we obtain new families of bivariate orthogonal functions and then compute their orthogonality relations via Parseval identity.