A New Generalization of Bivariate Sampling Kantorovich Operators and Applications to Image Processing

ABSTRACT In this paper, we introduce bivariate modified sampling Kantorovich operators, which extend the classical sampling Kantorovich operators by incorporating a transformation function . The paper begins by presenting essential definitions, including to introduce new bivariate weighted modulus of continuity, and its fundamental properties. The newly constructed operators are studied in terms of pointwise and uniform convergence in spaces of continuous functions. We investigate weighted approximation properties of the family of operators in weighted spaces of functions constructed by . Moreover, we study modular convergence of these operators in Orlicz spaces . Finally, we present some ‐kernels and applications to image processing. The newly constructed operators present better process and higher PSNR value for some parameters and function .

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Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2025-08-13
DOI
https://doi.org/10.1002/mma.70025
Citations
3
Primary Topic
Approximation Theory and Sequence Spaces
Type
article
Field-Weighted Citation Impact
7.89

Funders

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article

A New Generalization of Bivariate Sampling Kantorovich Operators and Applications to Image Processing

Tuncer Acar, Metin Turgay
3 citations
Mathematical Methods in the Applied Sciences
Approximation Theory and Sequence Spaces
7.89
article

A New Generalization of Bivariate Sampling Kantorovich Operators and Applications to Image Processing

Tuncer Acar, Metin Turgay
article en
3 citations

Abstract

ABSTRACT In this paper, we introduce bivariate modified sampling Kantorovich operators, which extend the classical sampling Kantorovich operators by incorporating a transformation function . The paper begins by presenting essential definitions, including to introduce new bivariate weighted modulus of continuity, and its fundamental properties. The newly constructed operators are studied in terms of pointwise and uniform convergence in spaces of continuous functions. We investigate weighted approximation properties of the family of operators in weighted spaces of functions constructed by . Moreover, we study modular convergence of these operators in Orlicz spaces . Finally, we present some ‐kernels and applications to image processing. The newly constructed operators present better process and higher PSNR value for some parameters and function .

Mathematical Methods in the Applied SciencesVol. 48(16)
Selçuk University (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Openalex Percentile: Top 2%
Approximation Theory and Sequence Spaces
7.89
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A New Generalization of Bivariate Sampling Kantorovich Operators and Applications to Image Processing — Tuncer Acar, Metin Turgay · Mathematical Methods in the Applied Sciences (2025) | TGRS Research Map | TGRS