An effective coded exposure photography framework using optimal fluttering pattern generation

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.