Kantorovich-Type Sampling Operators and Approximation

In this article, we investigate the convergence behavior of generalized sampling operators of Kantorovich-type. By combining the generalized sampling operators and Kantorovich sampling operators, we obtain the new composition operators and estimate the order of approximation. Then, we establish quantitative estimates for convergence in terms of the first-order modulus of continuity and K$$ K $$-functional. We also estimate the difference of these operators with generalized sampling operators. Moreover, we examine the order of approximation in the weighted space of continuity. Illustrative examples of kernels that meet the necessary assumptions are provided. We also demonstrate the performance of the proposed operators through graphical examples and numerical tables. Finally, we explore their potential applications in digital image processing.