Target extraction of blurred infrared image with an immune network template algorithm

• A coordination immune network template algorithm for extracting target from blurred infrared image is proposed.
• The topology of the algorithm reflects the coordination mechanism between innate immunity and adaptive immunity.
• The designing process of immune network template reflects the space-domain and the frequency-domain characteristics of the blurred infrared image.

To extract targets from blurred infrared images efficiently, this paper presents a coordinated immune network template algorithm based on the coordination mechanism between innate immunity and adaptive immunity. First, the neighbourhood characteristics for every pixel in a blurred infrared image are computed as the template features of each pixel. Next, all of the pixels are divided into three sets according to their grey level values: a target set, a background set and a blurred set. Finally, the pixels in the target set and the background set are used for training the adaptive network, which can divide each blurred pixel into two classes: a target pixel or a background pixel. Experimental results on the hand trace infrared images verified that the proposed algorithm could efficiently extract targets from images and produce better extraction accuracy.