The main focus of this paper is detection of steep changes in images. We propose a novel approach for detection of steep changes based on the Parzen kernel estimation of the partial derivatives of the multivariate regression functions in presence of random noise. The proposed algorithm is applied to one- and two-dimensional images to detect the abrupt changes within them. The experiments with different types of kernels are carried out to assess their effectiveness.