Abstract
Remote sensing images generally contain a large amount of information. For this, the researchers perform remote sensing image analysis by some computational methods. Modern geophysical monitoring is one of the main applications of remote control detection techniques. Among the essential tasks performed by these techniques is the detection of changes in physical geography and the study of forest issues. The purpose of this chapter is to analyze the most efficient methods used by remote sensing image processing tasks using traditional algorithms, optimization algorithms, and artificial intelligence algorithms. For this, this review includes corner detection techniques for image matching, endmember extraction for unmixing pixels, segmentation, and object classification. The purpose is to have a compendium of techniques developed in recent years.
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Ramos-Michel, A., Pérez-Cisneros, M., Cuevas, E., Zaldivar, D. (2020). A Survey on Image Processing for Hyperspectral and Remote Sensing Images. In: Oliva, D., Hinojosa, S. (eds) Applications of Hybrid Metaheuristic Algorithms for Image Processing. Studies in Computational Intelligence, vol 890. Springer, Cham. https://doi.org/10.1007/978-3-030-40977-7_2
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