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An efficient algorithm to update non-flat and incremental attributes in morphological trees
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AI
DOI：10.1016/j.patrec.2022.09.005.png)
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Attribute Filters are powerful image simplification operators that have very good contour-preservation properties. They can be efficiently computed using morphological trees. The most common strategy to compute attribute filters using morphological trees is based on three steps: (i) tree construction: the tree is built along with its attributes; ( ii ) filtering: we simplify the tree by removing some of its nodes based on some attribute and a filtering rule defined on a threshold value; and ( iii ) image reconstruction: this is the final phase where the tree is converted back to an image leading to an attribute filter. However, after filtering a few attributes in tree may change (we call them as non-flat attributes) and they must be updated, when other attribute filters are applied to the simplified tree again, with either a different or the same threshold value. In this paper we present an efficient algorithm to update non-flat and incremental attributes in morphological trees with low memory consumption and fast computation.(c) 2022 Elsevier B.V. All rights reserved.
Keyword:
Morphological trees
Attribute filters
Incremental Attributes
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IF:
3.3
论文数:
8.0K
被引数:
1.6W
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