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基于量子遗传优化算法的图像稀疏分解

李恒建 尹忠科 王建英

李恒建, 尹忠科, 王建英. 基于量子遗传优化算法的图像稀疏分解[J]. 西南交通大学学报, 2007, 20(1): 19-23.
引用本文: 李恒建, 尹忠科, 王建英. 基于量子遗传优化算法的图像稀疏分解[J]. 西南交通大学学报, 2007, 20(1): 19-23.
LI Hengjian, YIN Zhongke, WANG Jianying. Image Sparse Decomposition Based on Quantum Genetic Algorithm[J]. Journal of Southwest Jiaotong University, 2007, 20(1): 19-23.
Citation: LI Hengjian, YIN Zhongke, WANG Jianying. Image Sparse Decomposition Based on Quantum Genetic Algorithm[J]. Journal of Southwest Jiaotong University, 2007, 20(1): 19-23.

基于量子遗传优化算法的图像稀疏分解

基金项目: 

四川省重点科技计划项目(04GG021-020-5,03GG006-005-2)

教育部留学回国人员科研启动基金资助项目(教外司[2004]527号)

详细信息
    作者简介:

    李恒建(1980- ),男,博士研究生,研究方向为图像处理和智能算法.

    通讯作者:

    尹忠科(1969- ),男,教授,主要研究方向为信号与信息处理、图像处理,E-mail:zkyin@home.swjtu.edu.cn

Image Sparse Decomposition Based on Quantum Genetic Algorithm

  • 摘要: 为了减少图像稀疏分解的计算量,提出了一种基于量子遗传算法与匹配追踪相结合的图像稀疏分解快速算法.量子遗传算法能用较小的种群规模实现较大的空间搜索,全局寻优能力强,基于匹配追踪的图像稀疏分解是最优化问题,因此可用量子遗传算法快速实现.仿真结果表明,每步分解所需计算的图像或图像残差与原子的内积仅4 000次,由分解结果重建的图像具有较好的主观质量.

     

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出版历程
  • 收稿日期:  2005-12-15
  • 刊出日期:  2007-02-25

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