Dynamic autofocusing region selection based on improved PSO

Autofocusing region selection is an important module in autofocusing system, which directly influences the accuracy of focusing evaluation. For the traditional region-selection algorithms, such as central window and Gaussian non-uniformed sampling, exist some limitations, an algorithm based on particle swarm optimization (PSO) is proposed; for the standard particle swarm optimization is easy lost in local optimum, the parameters of PSO are improved in this paper. The results show that foreground image with edge information can be selected accurately, no matter it is in the center area or not. So the region is dynamic and adaptive. Further more, the real-time and antinoise performance of evaluation curve is improved.