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Image Classification via Hierarchical Dictionary Learning
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DOI：10.1109/ccdc.2019.8832839.png)
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Recently lots of dictionary learning methods have been presented to deal with the issue of image classification, there is still substantial room for improvement. To further improve the performance, a novel Fisher discriminative criterion based structured dictionary learning method is here introduced which contains the main two components. Firstly, category-unique dictionary for all categories in different levels arc learned to obtain the specific information of each category, and category-shared dictionary between all categories are learned in different levels to obtain the common information across different categories; secondly, a discriminative term in terms of Fisher discrimination criterion is here jointly utilized to enhance the discrimination of category-unique dictionary and category-shared dictionary. Experiment results on public available databases are conducted to demonstrate the superiority of the proposed method compared with the state-of-the-art dictionary learning methods.
Keyword:
Structured Dictionary Learning
Fisher Discriminative Criterion
Image Classification
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