A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inne...A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inner-level Bregmanized method devotes to dictionary updating and sparse represention of small overlapping image patches. The introduced constraint of graph regularized sparse coding can capture local image features effectively, and consequently enables accurate reconstruction from highly undersampled partial data. Furthermore, modified sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge within a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can effectively reconstruct images and it outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.展开更多
A series of sisal based activated carbon fibers were prepared with steam activation at temperature from 750℃ to 900℃. Their pore structures were characterized through their nitrogen adsorption isotherms at 77K using...A series of sisal based activated carbon fibers were prepared with steam activation at temperature from 750℃ to 900℃. Their pore structures were characterized through their nitrogen adsorption isotherms at 77K using different theories. The results showed that t-plot method and DR-plot method could suitably be used to characterize the mesopore structure and the multi-stage distribution of pore size of activated carbon fibers. It also showed that the pore size widens with the increase of activation temperature.展开更多
基金The National Natural Science Foundation of China (No.61362001,61102043,61262084,20132BAB211030,20122BAB211015)the Basic Research Program of Shenzhen(No.JC201104220219A)
文摘A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inner-level Bregmanized method devotes to dictionary updating and sparse represention of small overlapping image patches. The introduced constraint of graph regularized sparse coding can capture local image features effectively, and consequently enables accurate reconstruction from highly undersampled partial data. Furthermore, modified sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge within a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can effectively reconstruct images and it outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.
基金Natural Science Foundation Committee of Chinese government (grant No. 50073029) and by Guangdong Provincial Natural Science Foundation (001276)
文摘A series of sisal based activated carbon fibers were prepared with steam activation at temperature from 750℃ to 900℃. Their pore structures were characterized through their nitrogen adsorption isotherms at 77K using different theories. The results showed that t-plot method and DR-plot method could suitably be used to characterize the mesopore structure and the multi-stage distribution of pore size of activated carbon fibers. It also showed that the pore size widens with the increase of activation temperature.
