Research of unsupervised change detection means based on clustering characteristic of 2-D histogram

In this paper, a novel image change detection means is proposed based on the clustering characteristic of 2-D histogram. First, the best segmentation direction of 2-D histogram formed by pixel gray levels and the local average gray levels is ascertained by using LSM. Secondly, a kind of new 2-D entropy is defined to search the best threshold line and segment the 2-D histogram into unchanged region and change region. Then the change area in different image is detected based on the change region of 2-D histogram. Finally, the proposed means is compared to traditional means. The theoretical analysis and experiment results confirm the effectiveness of the proposed means.