In order to achieve robust dim and small target detection in the infrared cloud clutter

a new approach based on fuzzy classification is proposed. Different kinds of class regions are extracted from the query image to get several classification models

which can describe different classes in the image exactly. Classification based on such models will classify the image effectively and achieve robust dim and small target detection. Firstly

analysis of dim and small infrared target image is performed. Eleven kinds of class regions are proposed to describe sky

cloud and the target in the image. Then class feature vector and class kernel are defined. Class kernels of eleven class regions are extracted from the query image. At last

class similar coefficient and class similarity degree are defined according to the fuzzy classification theory. Image classification and class merge are performed. Target detection is achieved by reserving dim and small target class. Experimental results show that the proposed method describes different kinds of regions in the dim and small infrared target image effectively and provides robust dim and small infrared target detection in heavy background clutter.