Abstract Motion blurring often occurs during camera imaging process due to the relative motion between the scene and imaging sensor, which would degrade the quality of captured image. In this paper, an effective coded exposure photography framework is proposed to help obtain better motion deblurring results. An integrated optimal fluttering pattern generation criterion with several factors is designed to guarantee the limited frequency information loss using coded exposure photography. Furthermore, an effective fluttering code sequence search algorithm is put forward to obtain the optimal code sequence quickly with perfect balance consideration of global search and local search. The differential evolution algorithm is utilized to carry out effective global searching. Meanwhile, simulate annealing algorithm is introduce to implement supplementary local optimal search, which could help avoid falling into local optimizations and reduce the iteration numbers significantly. Various groups of synthetic and real-world deblurring experiments are carried out to verify the effectiveness of the designed imaging framework. Experimental results demonstrate that the optimal fluttering pattern could be calculated quickly by the presented approach and the deblurring images have superior subjective visual perception and objective image quality assessment performance.

中文翻译：

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使用最佳颤振图案生成的有效编码曝光摄影框架

摘要 在相机成像过程中，由于场景和成像传感器之间的相对运动，经常会发生运动模糊，这会降低所捕获图像的质量。在本文中，提出了一种有效的编码曝光摄影框架，以帮助获得更好的运动去模糊结果。设计了具有多个因素的集成最优颤振图案生成标准，以使用编码曝光摄影保证有限的频率信息丢失。在此基础上，提出了一种有效的颤动码序列搜索算法，可以在全局搜索和局部搜索的完美平衡下快速获得最优码序列。利用差分进化算法进行有效的全局搜索。同时，引入模拟退火算法实现补充局部最优搜索，避免陷入局部优化，显着减少迭代次数。进行了各种合成和现实世界的去模糊实验，以验证所设计的成像框架的有效性。实验结果表明，所提出的方法可以快速计算出最优抖动模式，并且去模糊图像具有优越的主观视觉感知和客观图像质量评估性能。