RECENT ADVANCES IN REMOTE SENSING IMAGE PROCESSING
Remote sensing image processing is nowadays a mature research area. The techniques developed in the ﬁeld allow many real-life applications with great societal value. For instance, urban monitoring, ﬁre detection or ﬂood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary ﬁeld of science that embraces physics, signal theory, computer science, electronics, and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under speciﬁc formalisms, such as classiﬁcation and clustering, regression and function approximation, image coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This paper serves as a survey of methods and applications, and reviews the last methodological advances in remote sensing image processing.
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