Image Processing Techniques for Remote Sensing

This chapter introduces the methods for signal and image processing used in a large number of applications in remote sensing. It presents the models and the so-called "low-level" processing that are closer to pixel level: the statistic models, and then the preprocessing, sampling, deconvolution and denoising. The chapter presents the statistical models that are necessary for certain segmentation, detection or classification techniques. It describes the segmentation methods and discusses the information extraction methods for punctual, linear and extended objects. Classification methods are exploited in image processing for image segmentation and object recognition. The chapter discusses classification methods and dimensionality reduction techniques. It concludes with a presentation of fusion methods.