Abstract
Remote sensing (RS) images are one of the main spatial data sources. The variability of image data types and their complex relationships are the main difficulties that face SDM. This chapter covers a combination of inductive learning and Bayesian classification to classify RS images, the use of rough sets to describe and classify images and extract thematic information; image retrieval based on spatial statistics; and image segmentation, facial expression analysis, and recognition utilizing cloud model and data field mapping.
Cite
CITATION STYLE
Li, D., Wang, S., & Li, D. (2015). Remote Sensing Image Mining. In Spatial Data Mining (pp. 257–297). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-48538-5_9
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