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A comparison between the sampling Kantorovich algorithm for digital image processing with some interpolation and quasi-interpolation methods. (English) Zbl 1433.65023

Summary: In this paper, we study the performance of the sampling Kantorovich (S-K) algorithm for image processing with other well-known interpolation and quasi-interpolation methods. The S-K algorithm has been implemented with three different families of kernels: central B-splines, Jackson type and Bochner-Riesz. The above method is compared, in term of PSNR (Peak Signal-to-Noise Ratio) and CPU time, with the bilinear and bicubic interpolation, the quasi FIR (Finite Impulse Response) and quasi IIR (Infinite Impulse Response) approximation. Experimental results show better performance of S-K algorithm than the considered other ones.

MSC:

65D18 Numerical aspects of computer graphics, image analysis, and computational geometry
65D05 Numerical interpolation
65D07 Numerical computation using splines
41A05 Interpolation in approximation theory
41A25 Rate of convergence, degree of approximation
47A58 Linear operator approximation theory
41A30 Approximation by other special function classes
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