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Structural Similarity Sparse Coding |
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PP: 363-369 |
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Author(s) |
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Zhiqing Li,
Weizhong Zhao,
Zhixin Li,
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Abstract |
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| Sparse coding theory demonstrates that the neurons in primary visual cortex form a sparse representation of natural scenes
in the viewpoint of statistics. In this paper, we propose a novel sparse coding model based on structural similarity for natural image
patch feature extraction. The advantage for our model is to be able to preserve structural information from a scene, which human visual
perception is highly adapted for. Using the proposed sparse coding model, the validity of image patch feature extraction is testified.
Furthermore, compared with standard sparse coding model, the experimental results show that the quality of reconstructed images
obtained by our method outperforms standard sparse coding model. |
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