Infrared image enhancement based on gray clustering algorithm

A new algorithm method of image enhancement based on K-means clustering is presented, according to the characteristics of infrared gray-image. In this method, firstly, the value of K is determined with the specific image, then the statistic analysis is carried out for the radiation temperature data of the infrared image to sort the data in ascending order, finally, the data of an arithmetical progression are selected as initial clustering centers and the temperature data are clustered by K-means algorithm with the generated clustering centers. At last, the self-adaptive enhancement is completed for the image with the clustering result. The satisfactory result is achieved in the experiment with gray infrared images. Compared with the histogram equalization method, the simulation result indicates that this method could further improve the visual effect, and provide detailed information and better gradation.