提出了一种基于Memetic算法的编码曝光最优码字序列搜索方法。分析了编码曝光成像理论模型,建立了最优码字选取的适应度函数准则。引入Memetic算法框架并开展了最优编码序列搜索,利用遗传搜索算法进行了全局最优解搜索,并在此基础上利用模拟退火算法进行了局部最优解求解,通过适应度函数的阈值约束及种群和最优解的更新迭代,得到了最优码字搜索结果。研究结果表明,相比其他方法,所提算法兼顾了全局最优与局部最优的求解,得到的最优码字序列具有更优性能指标,算法执行效率高,复原图像的主客观评价质量更好。

A searching method for an optimal code sequence of coded exposure is proposed based on the Memetic algorithm. The theoretical model for coded exposure imaging is analyzed and the criteria of fitness function for the optimal codeword selection is established. The Memetic algorithm framework is introduced to carry out the optimal code sequence search, and the genetic search algorithm is utilized to implement the global optimal solution search. On this basis, the simulated annealing algorithm is used to conduct the local optimal solution. The optimal codeword search results are obtained by the threshold constraint of the fitness function and the updated iteration of population and optimal solution. The research results show that, compared with other methods, the proposed algorithm can take into account both the global and the local optimal solutions, the obtained optimal code sequence has a better performance index, the execution efficiency is high, and the restored image has superior subjective and objective evaluation quality.