A probabilistic blur detection approach for the autofocus of infrared images

The infrared (IR) cameras plays an important role in the measurement and analysis of object signature. However, especially the scientific IR cameras that are used for research and military purposes have manual focusing system that reduces the sensitivity and reliability of the measurement taken. Camera autofocus algorithms extract various features from the camera images in order to define a measure for determining the most focused camera image instance. In this work, a no-reference image quality measure is modified and the modified measure is proposed for the autofocus of infrared cameras. Experimental results show that the proposed measure can be used in the problem of autofocus of infrared cameras, successfully.