The edge regularization of noised image method

Abstract

A model of extraction and regularization of edges of noisy images is presented. Edge is defined as a local maximum of the image gradient. The model is based on a formation of local dependences between pixels of the image, so called pattern and step dynamic approximation of the value of the brightness of individual pixels. The dynamics of the model are defined by an adequately constructed function of cost (further on called energy, due to an analogy with potential energy). Energy is specified from the use of the sum of adversities of scalar products of the neighboring vectors of the gradient. This process can be easily implemented in a cellular neuron network of a suitable design. Regularization of the image is an important phase of image processing among others image recognition.