The purpose of this study is to perform segmentation and noise removal in digital images of remote sensing. These images have become increasingly part of everyday life in order, which appear as a strategic tool for the future. The scanned images are used in weather forecasting, forest surveys, oceanographic, urban, agricultural and others. As a direct consequence of technological advances started in the last two decades, the development of theories aimed at a structural analysis of images from a computational point of view using as a tool essentially mathematical foundations. In this sense, the use of Partial Differential Equations in image processing has grown significantly in recent years. The basic idea is to modify a given image, curve or surface with a partial differential equation and obtain the expected results as the solution of this equation. In other words, the use of Partial Differential Equations in image processing, specifically in segmentation and elimination of noise, not only allows the use of good computational algorithms as well as the use of important theoretical results like existence and uniqueness of solution. The model used in this study was to Barcelos and Chen and numerical implementation of the model was performed with MATLAB. The idea of this study is purify the images and keep their main characteristics such as texture and preservation of edges.Pages: 7875-787
