Nonclassical Receptive Field Inhibition Applied to Image Segmentation

This paper presents a new model to perform a supervised image segmentation task. The proposed model is called segmentation and classification with receptive fields (SCRF) which is based on the concept of receptive fields that analyzes pieces of an image considering not only a pixel or group of them, but also the relationship between them and their neighbors. In order to work with the SCRF model, we propose a new artificial neural network, called I-PyraNet, which is a hybrid implementation of the recently described PyraNet and the nonclassical receptive fields inhibition. Furthermore, the model and the neural network are combined to accomplish a satellite image segmentation task.