The study of detecting for IR weak and small targets based on fractal features

Abstract

In the paper, the detection of IR weak and small targets is investigated in natural background based on fractal features. One feature of multi-scale variance ratio of fractal surface is proposed according to the fact that the fractal feature of man made objects changes shaper than the natural background. The new feature stands out the artificial objects much better from natural background than what can be done by fractal dimension feature or fractal model fit error feature, thus inhibiting background clutters well. Local gray histogram statistics is applied to object detection in the images with feature of multi-scale variance ratio of fractal surface. Experimental results shows that the detecting algorithm based on such a feature can localize weak and small objects stably in a single-frame image, and is a effective algorithm. © Springer-Verlag Berlin Heidelberg 2007.