Computation of local image derivatives is an important operation in many image processing tasks that
involve feature detection and extraction, such as edges, corners or more complicated features. However,
derivative computation in discrete images is an ill-posed problem and derivative operators without
any prior smoothing are known to enhance noise. Here we present a new convolution operator, the
GaussianDerivativeOperator, that allows to calculate locally Gaussian derivatives of N order. Furthermore,
we present some useful classes and examples that make use of this new operator.