In order to improve the effect of infrared image enhancement,an improved quantum particle swarm optimization algorithm is proposed. Firstly,the multi layer space structure of particle swarm optimization was constructed,and the particle running space was divided into the main layer space and the sub layer space. The particle information communication was carried out through the main layer space and the sub layer space respectively,and the communication process was affected by its own information degree factor and communication degree factor. Secondly,the quantum rotation gate was updated through the mirror gate operation,and the rotation angle of the quantum gate was adjusted through the gradient method adaptively,so that improved the algorithm performance. Finally,the high frequency and low frequency components of the infrared image were separated and enhanced respectively. The simulation results show that the improved quantum particle swarm optimization would enhance the infrared image which clearer than other algorithms,the evaluation index of high quality coefficient is improved 43.60%,36.52%,25.60%,19.24% and 12.14% respectively compared with HE,NSCT,MSR,PSO and RSQS,the contrast index is improved 27.99%,20.70%,15.28%,13.97% and 10.85% respectively compared with HE,NSCT,MSR,PSO and RSQS. It is proved that the performance index obtained by this algorithm is better than using other algorithms.
SONG Rui, LI Yu-xin. Infrared image enhancement based on improved quantum particle swarm optimization[J]. LASER & INFRARED,2021,51(11):1531~1537