Abstract:Rayleigh functions σ l (ν) are defined as series in inverse powers of the Bessel function zeros λ ν,n = 0, σ l (ν) = ∞ n=1 1 λ 2l ν, n , where l = 1, 2, . . . ; ν is the index of the Bessel function J ν (x) and n = 1, 2, . . . is the number of the zeros. Convolutions of Rayleigh functions with respect to the Bessel index, R l (m) = ∞ k=−∞ σ l |m − k| σ l |k| for l = 1, 2, . . . ; m = 0, ±1, ±2, . . . , are needed for constructing global-in-time solutions of semi-linear evolution equations in circular domains [… Show more
“…Thus, the underlying principle is to use a different decaying function to achieve smoothing in the domain filter; rather than the Gaussian function [30]- [31]. Rayleigh distribution function can be regarded as both real and imaginary parts of the complex signal which is corrupted with zero mean uncorrelated Gaussian noise.…”
Section: Proposed Filtering Methods a Proposed (Modified) Bilatermentioning
Digital photography provides a quick and facile means to capture a pair of images i.e. flash and no-flash image. Digital images are often superimposed by noises at the acquisition stage depending upon the availability of lighting. Image denoising is a key technology to reduce the noise levels from the images while preserving the fine details and structures. Predominantly, conventional Bilateral filter is employed, providing better noise reduction capabilities with low noise density while preserving the edges. The spatial processing of pixels is reckoned by using a Gaussian function (symmetric and smoothly decaying function). This paper introduces a Bilateral filter which incorporates a Rayleigh distribution function in its domain filter to smoothen out the image pairs more effectively. This filter has been implemented on both the images (flash and no-flash) in the present work. Simulations are carried out on the images contaminated with different levels of Gaussian noise and are evaluated on the basis of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) as image quality parameters. Performance of the proposed filter has shown significant results when compared to the conventional Bilateral filter.
“…Thus, the underlying principle is to use a different decaying function to achieve smoothing in the domain filter; rather than the Gaussian function [30]- [31]. Rayleigh distribution function can be regarded as both real and imaginary parts of the complex signal which is corrupted with zero mean uncorrelated Gaussian noise.…”
Section: Proposed Filtering Methods a Proposed (Modified) Bilatermentioning
Digital photography provides a quick and facile means to capture a pair of images i.e. flash and no-flash image. Digital images are often superimposed by noises at the acquisition stage depending upon the availability of lighting. Image denoising is a key technology to reduce the noise levels from the images while preserving the fine details and structures. Predominantly, conventional Bilateral filter is employed, providing better noise reduction capabilities with low noise density while preserving the edges. The spatial processing of pixels is reckoned by using a Gaussian function (symmetric and smoothly decaying function). This paper introduces a Bilateral filter which incorporates a Rayleigh distribution function in its domain filter to smoothen out the image pairs more effectively. This filter has been implemented on both the images (flash and no-flash) in the present work. Simulations are carried out on the images contaminated with different levels of Gaussian noise and are evaluated on the basis of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) as image quality parameters. Performance of the proposed filter has shown significant results when compared to the conventional Bilateral filter.
“…(25) in Wu et al [29, p. 6]. Varlamov [26,27] systematically investigated convolutions of the Rayleigh functions with respect to the Bessel index and attempted to exhibit their usefulness for constructing global-in-time solutions of semi-linear evolution equations in circular domains.…”
Section: Series Expressible In Terms Of the ψ-Functionmentioning
confidence: 99%
“…v being the index of the Bessel function J v (x) whose zeros are λ v,n . Varlamov [26,27] succeeded in treating the Rayleigh functions σ l (v) as special functions by presenting some references for functions of the Rayleigh type as well as in their own right (see the references cited by Varlamov [26,27]).…”
Section: Wwwmn-journalcom 3 Convolutions Of the Rayleigh Functionsmentioning
confidence: 99%
“…Varlamov [27] also presented a general formula for R l (m) in terms of σ l (v) and expressed R 2 (m) in terms of the ψ-function, together with its asymptotic formula as |m| → ∞, by making use of the ψ-function, as follows: expression:…”
Section: Wwwmn-journalcom 3 Convolutions Of the Rayleigh Functionsmentioning
confidence: 99%
“…Furthermore, Varlamov [27] provided an example of an initial-boundary-value problem leading to an explicit appearance of R 1 (m) and R 2 (m). In order to show a usefulness of the polygamma functions, we express R 3 (m) in terms of the polygamma functions and give its asymptotic formula as |m| → ∞.…”
Section: Wwwmn-journalcom 3 Convolutions Of the Rayleigh Functionsmentioning
The Gamma function and its nth logarithmic derivatives (that is, the polygamma or the psi-functions) have found many interesting and useful applications in a variety of subjects in pure and applied mathematics. Here we mainly apply these functions to treat convolutions of the Rayleigh functions by recalling a general identity expressing a certain class of series as psi-functions and to evaluate a class of log-sine integrals in an algorithmic way. We also evaluate some Euler sums and give much simpler psi-function expressions for some known parameterized multiple sums.
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