Convolution multipliers and distributions

Approximate convolution using DCT coefficient multipliers

DCT-domain processing, filtering, convolution, image enhancement, quantization tables We develop a method for designing DCT coefficient multipliers in order to approximate the operation of 2D convolution of an image with a given kernel. The method is easy to implement on compressed formats of DCT-based compression methods (JPEG, MPEG, H.261) by applying decoding quantization tables that are inc...

On Generalized Gamma Convolution Distributions

We present here characterizations of certain families of generalized gamma convolution distributions of L. Bondesson based on a simple relationship between two truncated moments. We also present a list of well-known random variables whose distributions or the distributions of certain functions of them belong to the class of generalized gamma convolutions. Mathematics Subject Classification 2000...

On the Convolution of Gamma Distributions

In this paper, we give a formula for the distribution of the sum of n independent random variables with gamma distributions. A formula for such a sum was provided by Mathai (see [5]) in 1982. But it was complicated. In the paper [1], Jasiulewicz and Kordecki derived a formula for the particular case of independent random variables having Erlang distributions by using Laplace transform. Our meth...

Infinite Convolution Products and Refinable Distributions on Lie Groups

Sufficient conditions for the convergence in distribution of an infinite convolution product μ1 ∗μ2 ∗ . . . of measures on a connected Lie group G with respect to left invariant Haar measure are derived. These conditions are used to construct distributions φ that satisfy Tφ = φ where T is a refinement operator constructed from a measure μ and a dilation automorphism A. The existence of A implie...

On the Multipli ation and Convolution of Homogeneous Distributions