Multivariate Generalized Gamma-Type Operators: Approximation Results and Applications to Image Processing

In the present paper, we extend a class of integral operators of probabilistic type, which are constructed by means of the generalized Gamma distribution, to the multidimensional setting. In particular, we discuss their approximation properties in weighted continuous function spaces for a broad range of weights, as well as some shapepreserving properties for them. A graphical example is also shown. The paper concludes with applications to image processing, comparing the performance of the new operators, in terms of image denoising, with other well-established denoising techniques