Image analysis classification and change detection in remote sensing pdf
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Change detection using object features
Object-Based Image Analysis pp Cite as. For the detection of changes, several statistical techniques exist. When adopted to high-resolution imagery, the results of traditional pixel-based algorithms are often limited. We propose an unsupervised change detection and classification procedure based on object features. Following the automatic pre-processing of the image data, image objects and their object features are extracted. Change detection is performed by the multivariate alteration detection MAD , accompanied by the maximum autocorrelation factor MAF transformation. The change objects are then classified using the fuzzy maximum likelihood estimation FMLE.
Skip to main content Skip to table of contents. Advertisement Hide. Front Matter Pages Object-based image analysis for remote sensing applications: modeling reality — dealing with complexity. Pages Progressing from object-based to object-oriented image analysis.
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