Adaptive infrared image enhancement based on fuzzy particle swarm optimization algorithm
Zhang Shu-ling · Computer Engineering and Applications Journal · 2008
Considering the characteristics of the inconspicuous difference between targets and backgrounds and the low contrast in infrared images,an adaptive enhancement algorithm based on fuzzy particle swarm optimization is used in the infrared image processing.The gray transformation is better one of the infrared image enhancement methods,but the suitable threshold is powerful guarantee for obtaining the good enhancement effect.Under the maximal entropy criterion,the auto-adapted threshold is selected by particle swarm optimization.Then using fuzzy gray transformation,the infrared image gray is auto-adapted stretched and image is enhanced.Experiments show that compared with histogram equalization,the presented algorithm can reduce the background influence over the goal and improve the contrast of infrared imagery.