A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
"The Discrete Fourier Transform (DFT) can be understood as a numerical approximation to the Fourier transform. However, the DFT has its own exact Fourier theory, which is the ...
After the emergence of numerous Internet streaming applications, rate-distortion (R-D) modeling of scalable video encoders has become an important issue. In this paper, we examine...
This paper introduces a new generalisation of scale-space and pyramids, which combines statistical modelling with a spatial representation. The representation uses the familiar co...
In this paper, we apply the complexity?regularization principle to Poisson imaging. We formulate a natural distortion measure in image space, and present a connection between comp...