Research of unsupervised image change detection algorithm based on 2-D histogram

Change detection in images of a given scene acquired at different times is one of the most interesting topics of remote image processing. In this paper, a novel image change detection algorithm is proposed based on the clustering characteristic of 2-D histogram. First, the best segmentation direction of 2-D histogram is ascertained by using Fisher criterion. Secondly, a kind of new 2-D entropy is defined to search the best threshold 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 algorithm is compared to traditional algorithm. The theoretical analysis and experiment results confirm the effectiveness of the proposed means.