Hierarchical image representation via multi-level sparse coding
ICIP(2014)
摘要
This paper presents a hierarchical model for robust image representation. We first introduce multi-level sparse coding algorithm and normalized max pooling strategy which are designed to obtain meaningful sparse codes and robust pooled codes, respectively. With the sparse codes and pooled codes, a hierarchical architecture is built and more robust features are extracted at the second layer. The proposed method has been evaluated on two widely used datasets: Caltech-101 and Caltech-256, and experimental results demonstrate that the proposed method is both effective and robust in image representation compared with the state-of-the-art.
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关键词
hierarchical,image representation,image coding,multilevel sparse coding,hierarchical image representation,normalized max pooling strategy,multi-level sparse coding,caltech-256,caltech-101,normalized max pooling,robust pooled codes,robust image representation
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