Weighted Norm Inequalities for Fractional Integral Operators With Rough Kernel

Depth images are often accompanied by unavoidable and unpredictable noise. Depth image denoising algorithms mainly attempt to fill hole data and optimise edges. In this paper, we study in detail the problem of effectively filtering the data of depth images under noise interference. The classical filtering algorithm tends to blur edge and texture information, whereas the fractional integral operator can retain more edge and texture information. In this paper, the Grünwald–Letnikov-type fractional integral denoising operator is introduced into the depth image denoising process, and the convolution template of this operator is studied and improved upon to build a fractional integral denoising model and algorithm for depth image denoising. Depth images from the Redwood dataset were used to add noise, and the mask constructed by the fractional integral denoising operator was used to denoise the images by convolution. The experimental results show that the fractional integration order with the best denoising effect was −0.4 ≤ ν ≤ −0.3 and that the peak signal-to-noise ratio was improved by +3 to +6 dB. Under the same environment, median filter denoising had −15 to −30 dB distortion. The filtered depth image was converted to a point cloud image, from which the denoising effect was subjectively evaluated. Overall, the results prove that the fractional integral denoising operator can effectively handle noise in depth images while preserving their edge and texture information and thus has an excellent denoising effect.

Fractional calculus, particularly fractional integral operators, has gained significant attention in recent years due to its wide-ranging applications in various scientific disciplines.This paper provides a comprehensive review of the latest advancements in fractional integral operators, covering theoretical developments, practical applications, and computational methods.We explore the mathematical foundations of fractional integrals, discuss their applications in diverse fields such as signal processing, mathematical physics, and image processing, and examine state-of-the-art computational techniques for their efficient computation.Additionally, we highlight current research trends and future directions in the field of fractional integral operators. I. INTRODUCTIONFractional calculus, a branch of mathematics that generalizes the concepts of differentiation and integration to non-integer orders, has garnered increasing attention in recent years due to its versatile applications across diverse scientific disciplines.Central to the theory of fractional calculus are fractional integral operators, which play a pivotal role in describing non-local and memory-dependent phenomena in complex systems.In this paper, we present a comprehensive review of the latest advancements in fractional integral operators, encompassing theoretical developments, practical applications, and computational methods.Theoretical Foundations of Fractional Integrals, Fractional integral operators, such as the Riemann-Liouville and Caputo integrals, are fundamental tools in fractional calculus.We begin by examining the mathematical foundations of fractional integrals, including their definitions, properties, and relationships with fractional derivatives [1,2].Additionally, we explore important theoretical results related to fractional integrals, such as their behaviour in function spaces and their connection to fractional differential equations [3,4].Applications of Fractional Integrals, Fractional integral operators find applications across a wide range of scientific disciplines, including signal processing, mathematical physics, and image processing.Recent research has demonstrated their utility in modelling anomalous diffusion phenomena [5], describing fractal behaviour in complex systems [6], and analysing non-local effects in viscoelastic materials [7].Moreover, fractional integrals have been applied to noise reduction, feature extraction, and data compression in signal and image processing applications [8,9].Computational Methods for Fractional Integrals, Efficient computation of fractional integrals is essential for their practical use in scientific research and engineering applications.We survey state-of-the-art computational methods for approximating fractional integrals, including numerical integration techniques, spectral methods, and fractional calculus software packages [10,11].Additionally, we discuss challenges and considerations in implementing these methods and provide insights into their computational complexity and accuracy.Current Research Trends and Future Directions, despite significant advancements in the theory and applications of fractional integral operators, several research avenues remain unexplored.Current research trends in the field include the application of fractional calculus to machine learning and data science [12], as well as the development of novel computational methods for solving fractional differential equations [13].Chinta Mani Tiwari (2006).Given A note on Dirac delta function [14], again Chinta Mani Tiwari.(2007).Worked on the Neutrix product of three distributions [15], recently Chinta Mani Tiwari (2023).explained Generalized function and distribution [19].Future research directions may focus on exploring emerging applications and addressing theoretical challenges in the analysis of complex systems using fractional integral operators.In summary, fractional integral operators represent a powerful mathematical tool with widespread applications in science and engineering.By providing a comprehensive overview of theoretical foundations,

Weighted norm inequalities for pseudo-pseudodifferential operators defined by amplitudes

<abstract> In this paper, the author studies the boundedness for a large class of sublinear operators $ T_\alpha, \alpha\in[0, n) $ generated by Calderón-Zygmund operators ($ \alpha=0 $) and generated by fractional integral operator ($ \alpha&gt;0 $) on generalized mixed Morrey spaces $ M^\varphi_{\vec{q}}({\mathbb R}^n) $. Moreover, the boundeness for commutators of $ T_\alpha, \alpha\in[0, n) $ on generalized mixed Morrey spaces $ M^\varphi_{\vec{q}}({\mathbb R}^n) $ is also studied. As applications, we obtain the boundedness for Hardy-Littlewood maximal operator, Calderón-Zygmund singular integral operators, fractional integral operator, fractional maximal operator and their commutators on generalzied mixed Morrey spaces. </abstract>

The Meda inequality for rearrangements of the convolution operator on the Heisenberg group is proved. By using the Meda inequality, an O'Neil-type inequality for the convolution is obtained. As applications of these results, some sufficient and necessary conditions for the boundedness of the fractional maximal operator and fractional integral operator with rough kernels in the spaces are found. Finally, we give some comments on the extension of our results to the case of homogeneous groups.

In this note we study the boundedness of \(p\)-adic fractional integral operator with rough kernels on \(p\)-adic Herz spaces. Moreover, we establish Lipschitz estimates for commutators of \(p\)-adic fractional integral operator with rough kernels on Herz spaces. In addition, we also obtain central bounded mean oscillations\((C{\dot{M}}O)\) estimate for commutators of \(p\)-adic fractional integral operator with rough kernels on \(p\)-adic Herz spaces. As an application, we characterize \(p\)-adic Herz space in terms of wavelets in continuously differentiable functions \(({\mathcal {C}}^{1}({\mathbb {Q}}_p^n))\) with compact support.

The article proposes a generalized polynomial projection method for solving linear integral equations with a fractional Riemann - Liouville integral in the main part. Fractional-integral equations have numerous applications in various applied problems, in particular, in problems of plasma diagnostics, optical and X-ray diffraction, in ultrasonic measurements in moving media, in metallurgy, biology, microscopy, seismology, in astrophysics and other fields of science.The equation we are considering is an equation of the first kind and therefore, generally speaking, refers to incorrectly set by Hadamard equations. The latter circumstance is connected with the fact that in known function spaces the fractional integral Riemann-Liouville operator is completely continuous. All this imposes its own characteristics on the construction and study of approximate methods for solving integral equations with a fractional integral operator in the main part. It should be noted that the operator of the projection method is not necessarily projective, which allows the construction of computational schemes using the methods of summation of Fourier series and interpolation polynomials. A theoretical and functional substantiation of the proposed projection method was carried out, based on the correct formulation of the equation in a pair of specially selected different Holder spaces. In particular, it proved the unique solvability of the system of linear algebraic equations of the method and the convergence of the constructed approximations to the exact solution in the norm of the space of Holder functions and, as a consequence, in the uniform metric. This also implies the substantiation of specific well-known projection methods such as the Galerkin methods, colocations, and subdomains.

A Fractional integral operator is one of the operators in mathematical analysis. Fractional integral operator itself maps any real-valued function into the integral form of the division of the at function. One of the expansion of fractional integral operator is generalized fractional integral operator. Morrey space is an extension of Lebesgue space. Morrey space is the set of all Lebesgue measurable functions, whose norm is finite over Morrey space. In this study, we will discuss the inequalities of the generalized fractional integral operator on a generalized non-homogeneous Morrey space. We proved of this inequality using the Chebyshev inequality and the Holder inequality.

Performing a thought study of fractional inequalities by means of convexity and fractional operators has conspicuous work in the field of analysis. The main object of this paper is to discuss the coordinated convexity, pre-invexity, and also establish fractional double integral operators (FDIO) having generalized Bessel-Maitland function as used its kernel. We develop a new generation of Hermite-Hadamard (H-H) and trapezoid-type inequalities through different types of coordinated convexities and pre-invexities with successfully implementation of newly designed fractional double integral operators. Moreover, we extract some corollaries, which are generalization of well-known inequalities for different coordinated convexities that show a strong consolidation of our main results.

The aim of this paper is to get the productLp${L}^{p}$-estimates, weighted estimates and two-weighted estimates for rough multilinear fractional integral operators and rough multi-sublinear fractional maximal operators, respectively. The author also studies two-weighted weak type estimate on productLp(ℝn)${L}^{p}\left({\mathrm{\mathbb{R}}}^{n}\right)$for rough multi-sublinear fractional maximal operators. In fact, this article is the rough kernel versions of [C. E. Kenig and E. M. Stein, “Multilinear estimates and fractional integration,”Math. Res. Lett., vol. 6, pp. 1–15, 1999, Y. Shi and X. X. Tao, “WeightedLp${L}_{p}$boundedness for multilinear fractional integral on product spaces,”Anal. Theory Appl., vol. 24, no. 3, pp. 280–291, 2008]'s results.

In this paper, we establish BMO estimates for generalized commutators of rough fractional maximal and integral operators on generalized weighted Morrey spaces, respectively.

The aim of the present paper is to optimize the values of different parameters related to the image denoising algorithm involving Caputo Fabrizio fractional integral operator of non-singular type with the Mittag-Leffler function in generalized form. The algorithm aims to find the coefficients of a kernel to remove the noise from images. The optimization of kernel coefficients are done on the basis of different numerical parameters like Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structure Similarity Index measure (SSIM) and Image Enhancement Factor (IEF). The performance of the proposed algorithm is investigated through above-mentioned numeric parameters and visual perception with the other prevailed algorithms. Experimental results demonstrate that the proposed optimized kernel based on generalized fractional operator performs favorably compared to state of the art methods. The uniqueness of the paper is to highlight the optimized values of performance parameters for different values of fractional order. The novelty of the presented work lies in the development of a kernel utilizing coefficients from a fractional integral operator, specifically involving the Mittag-Leffler function in a more generalized form.

We prove that if the exponent function p(\cdot) satisfies log-Hölder continuity conditions locally and at infinity, then the fractional maximal operator M_\alpha , 0 &lt; \alpha &lt; n , maps L^{p(\cdot)} to L^{q(\cdot)} , where \frac{1}{p(x)}-\frac{1}{q(x)}=\frac{\alpha}{n} . We also prove a weak-type inequality corresponding to the weak (1,n/(n-\alpha)) inequality for M_\alpha . We build upon earlier work on the Hardy-Littlewood maximal operator by Cruz-Uribe, Fiorenza and Neugebauer [The maximal function on variable L^p spaces. Ann. Acad. Sci. Fenn. Math. 28 (2003), 223-238]. As a consequence of these results for M_\alpha , we show that the fractional integral operator I_\alpha satisfies the same norm inequalities. These in turn yield a generalization of the Sobolev embedding theorem to variable L^p spaces.

In this paper, we derive some subordination and superordination results for the generalized "Srivastava-Attiya" fractional integral operator. Some interesting corollaries for this operator is also obtained.

In the framework of rational Dunkl analysis on the real line, we introduce Dunkl-type Besov-Fofana spaces which include Besov-Dunkl spaces and Dunkl-type Besov-Morrey spaces.As applications, we establish the boundedness of Dunkl-type fractional integral and fractional maximal operators in these spaces.