Research And Application Of Remote Sensing Image Change Detection Technology

Remote sensing image change detection is the process of using appropriate image processing technology to extract and analyze the difference information of remote sensing images as the surface of the same area has different characteristics at different times. Currently, remote sensing image change detection has been widely used in many fields, such as resource investigation and application, regional planning and layout, environmental testing and evaluation, military reconnaissance and combat effectiveness evaluation and so on. So this paper studies on the thorough research to the multi temporal remote sensing image change detection technology.The content of this paper mainly includes the following aspects:(1) A variety of algorithms for remote sensing image change detection are introduced in this paper, Firstly of all, the algorithm principle and the model architecture of the adaptive pulse coupled neural network(PCNN) are introduced and compared with other image fusion algorithms to highlight the PCNN technology has a better fusion effect. Then, the traditional C-V model and a new C-V model algorithm are proposed, and the paper also compares with other image segmentation techniques to illustrate the accuracy of this method.(2) Based on the above two kinds of the most high-quality algorithm, an algorithm based on adaptive pulse coupled neural network(PCNN) and improved Chan-Vese(C-V) model is proposed. This algorithm is to make the difference operation and the ratio operation between the two remote sensing images, then make the two operated images are processed by the improved adaptive PCNN image fusion algorithm. Finally, make the fused image segmented by the new C-V model algorithm which can get the image change detection results image. In this paper, the new algorithm is verified by experiments and compared with other algorithm, it is proved that the new algorithm has better detection results.(3) In order to better monitor the situation of the landslide changes and reduce the disaster, it is necessary to adopt the new remote sensing image change detection method based on adaptive PCNN image fusion algorithm and the improved C-V model segmentation algorithm. In this paper, the data before and after the Ludian earthquake are detected, the result shows that the proposed algorithm is very effective for the detection of landslide hazards.