MP-based images sparse decomposition by simulated annealing

  • Authors:

  • Xing-Xing Gao;Xian-Bin Wen;Li-Li Liu

  • Affiliations:

  • Key Laboratory of Computer Vision and System of Ministry of Education, Tianjin University of Technology, Tianjin, China and Tianjin Key Laboratory of Intelligence Computing and Novel Software Tech ...;Key Laboratory of Computer Vision and System of Ministry of Education, Tianjin University of Technology, Tianjin, China and Tianjin Key Laboratory of Intelligence Computing and Novel Software Tech ...;Key Laboratory of Computer Vision and System of Ministry of Education, Tianjin University of Technology, Tianjin, China and Tianjin Key Laboratory of Intelligence Computing and Novel Software Tech ...

  • Venue:
  • ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
  • Year:
  • 2010

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Abstract

Images sparse representation is very suitable for image processing, but the computational burden in images sparse decomposition process is very huge. A fast algorithm is presented based on Matching Pursuit (MP) images sparse decomposition. Simulated Annealing (SA) is applied to effectively search in the dictionary of atoms (i.e. overcomplete dictionary) for the best atom at each step of MP. Experiment results show that the performance of the proposed algorithm is very good.