Research of Unsupervised Image Change Detection Algorithm Based on Clustering Characteristic of 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, which finds important applications in many fields. In this paper, a novel image change detection algorithm was 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 was ascertained by using LSM. Secondly, a kind of new 2-D entropy was defined to search the best threshold line and segment the 2-D histogram into unchanged and change region. Then the change area was detected based on the change region of 2-D histogram. Finally, the proposed algorithm was compared to traditional change detection algorithm by carrying out an experiment on a synthetic data set generated artificially. Theoretical analysis and experiment result show that the proposed algorithm is more accurate on detection precision, and faster on detection speed.
Keyword-Change detection 2-D histogram Clustering characteristic 2-D maximal entropies
Wenbang Sun Hexin Chen Li Xue Qinling Liu
School of Communication Engineering, Jilin University Aviation University of Air Force Changchun Chi Unit of 61135 The Chinese Peoples Liberation Army Beijing China
国际会议
长春
英文
341-344
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）