Abstract
Image classification techniques are often used to reduce the large data volume content of an image to a simplified version - a thematic map, which can be more suitable from the user´s point of view. However, the delimitation of specific regions using unsupervised classification techniques frequently generates an excessive number of clusters or classes. The resulting image can be simplified by a process of hierarchical aggregation of the initial classes, yielding a set of classified images. This set of thematic maps can provide a powerful insight into the image content, as long as an adequate visualization strategy is used. This paper presents methodologies for the visualization of hierarchically structured classified images.
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Mesquita, T.A., Marçal, A.R.S. (2013). Hierarchic Image Classification Visualization. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_18
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DOI: https://doi.org/10.1007/978-3-642-39094-4_18
Publisher Name: Springer, Berlin, Heidelberg
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