Structural Similarity Sparse Coding and Image Feature Extraction
LI Zhi-Qing1,2,3,SHI Zhi-Ping1,LI Zhi-Xin1,2,SHI Zhong-Zhi1
1.Key Laboratory of Intelligent Information Processing,Institute of Computing Technology Chinese Academy of Sciences,Beijing 100190 2. Graduate University of Chinese Academy of Sciences,Beijing 100049 3. College of Information Engineering,Xiangtan University,Xiangtan 411105
Abstract The structural similarity is introduced into sparse coding model, and a sparse coding model based on structural similarity is proposed. Then, the model is employed to extract the image sparse coding feature. The experimental results show that the improved sparse coding model is consistent with human visual system for its capacity of structural information preservation. Furthermore, compared with the standard sparse coding model, the proposed model attains the reconstructed image which preserves better structural information of the original image.
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2010, Vol. 23 
